<div><strong>As a Principal Engineer in AI Security, you will define and lead Thrivent’s strategy for defending against emerging external AI-powered threats. This role focuses on protecting the enterprise from adversarial AI capabilities, including automated vulnerability discovery, exploitation, and AI-driven attack campaigns. You will operate at the intersection of cyber defense, artificial intelligence, and enterprise architecture, translating rapidly evolving external threats into practical, scalable protections across the organization. This role requires deep technical expertise, strong systems thinking, and the ability to influence security strategy at the highest levels.<br></strong><br></div><h3>DUTIES &amp; RESPONSIBILITIES:</h3><div><br><strong>Designing Solutions</strong></div><ul><li>Apply expert-level knowledge of AI-driven threats, cyber defense, and enterprise security architecture to define and drive outcomes that protect the organization from emerging AI-powered attack vectors.</li><li>Create the enterprise strategy for defending against AI-enabled threats, including automated vulnerability discovery, exploitation, and adversarial AI techniques.</li><li>Establish architecture for detection, prevention, and response capabilities specific to generative AI threat patterns.</li><li>Define and implement security patterns and guardrails to enable safe and secure enterprise consumption of AI technologies.</li><li>Drive integration of AI threat detection and controls into existing cyber defense tooling and platforms.</li><li>Build threat models focused on generative AI attack patterns and emerging adversarial techniques.</li></ul><div><br><strong>Implementing Solutions</strong></div><ul><li>Use independent, critical thinking to translate evolving AI threat intelligence into scalable engineering controls and defensive capabilities.</li><li>Lead the development of detection and response mechanisms for AI-driven attacks across enterprise environments.</li><li>Design and implement telemetry strategies to identify anomalous behavior indicative of AI-enabled threats.</li><li>Partner with Cyber Defense teams to operationalize detections, response playbooks, and automation for AI-related incidents.</li><li>Prototype and evaluate defensive applications of AI to enhance detection, response, and security operations.</li><li>Develop architecturally significant components that advance the organization’s ability to defend against AI-driven adversaries.</li></ul><div><br><strong>Learning and Applying New Techniques</strong></div><ul><li>Lead research initiatives focused on emerging AI threat capabilities, adversarial AI techniques, and evolving attack methodologies.</li><li>Maintain deep expertise in industry frameworks such as OWASP LLM Top 10 and MITRE ATLAS.</li><li>Continuously evaluate and introduce modern security technologies and approaches to address AI-era risks.</li><li>Drive adoption of innovative defensive techniques across the organization to stay ahead of threat evolution.</li></ul><div><br><strong>Collaborating Within the Team</strong></div><ul><li>Provide deep technical expertise in AI security to solve complex, high-impact problems and remove critical technical roadblocks.</li><li>Partner with product owners and engineering teams to incorporate AI security requirements into technical designs and user stories.</li><li>Act as a technical leader in system design across teams, ensuring AI security considerations are embedded into broader architecture decisions.</li><li>Mentor engineers and elevate AI security capabilities within teams.</li></ul><div><br><strong>Collaborating Across Teams</strong></div><ul><li>Partner closely with Cyber Defense, IAM, and Application Security teams to integrate AI threat protections across the security ecosystem.</li><li>Promote adherence to enterprise security standards while extending them to address AI-specific risks.</li><li>Broker design and implementation of AI security controls across product teams to support strategic priorities.</li><li>Drive alignment across teams on detection engineering, telemetry, and response strategies for AI threats.</li></ul><div><br><strong>Collaborating Across the Organization</strong></div><ul><li>Influence senior leadership on AI risk posture, threat landscape evolution, and required investments in defensive capabilities.</li><li>Provide enterprise-wide guidance on AI security architecture, ensuring consistent and scalable protection strategies.</li><li>Represent the organization externally on AI security topics when appropriate (industry forums, partnerships, etc.).</li><li>Translate complex AI security risks into actionable insights for both technical and non-technical stakeholders.</li></ul><div><br><strong>Setting Product/Platform Technology Strategy</strong></div><ul><li>Define enterprise-level capabilities required to defend against AI-powered threats.</li><li>Shape the strategic direction for AI security across cyber defense, detection engineering, and secure AI adoption.</li><li>Provide subject matter expertise to guide platform and security investments related to AI risk mitigation.</li></ul><div><br><strong>Defining Engineering Standards/Patterns</strong></div><ul><li>Establish and promote engineering standards for AI security, including secure AI usage patterns and detection frameworks.</li><li>Collaborate across teams to ensure consistent application of AI security controls and design patterns.</li><li>Drive adoption of best practices for integrating AI threat protections into engineering workflows and platforms.</li></ul><div><br><strong>DevOps</strong></div><ul><li>Provide technical leadership in identifying and responding to AI-driven security incidents and emerging threats.</li><li>Introduce resilient and scalable technologies to improve detection and response capabilities for evolving attack patterns.</li><li>Evaluate and implement enhancements to CI/CD and operational pipelines to incorporate AI security controls.</li><li>Influence cross-functional teams to proactively address risks associated with AI-enabled development and deployment.</li></ul><div><br><strong>Selecting and Managing Technology Vendors</strong></div><ul><li>Provide technical expertise in evaluating AI security tools, detection platforms, and emerging defensive technologies.</li><li>Assess how vendor solutions align with enterprise strategy for defending against AI-driven threats.</li><li>Contribute to selection criteria for platforms that enhance AI security posture and detection capabilities.</li></ul><div><br><strong>Coaching Engineers</strong></div><ul><li>Mentor engineers in AI security concepts, threat modeling, and detection engineering.</li><li>Provide guidance on best practices for securing AI-enabled systems and defending against adversarial AI techniques.</li><li>Deliver training, workshops, and knowledge-sharing sessions to build AI security expertise across the organization.</li></ul><div><br><strong>Recruiting and Building Talent</strong></div><ul><li>Engage in the broader AI and security community to strengthen organizational expertise and visibility in AI security.</li><li>Support recruitment efforts to hire engineers with specialized skills in AI security and advanced cyber defense.</li><li>Model Thrivent’s leadership competencies: Model the Way, Rally the Team, and Deliver Outcomes.</li><li>Foster a culture of continuous improvement, innovation, and strong security practices aligned to evolving AI risks.</li></ul><div><br><strong>QUALIFICATIONS &amp; SKILLS:</strong></div><h3>Required:</h3><ul><li>Bachelor's degree in Computer Science, Cybersecurity, or related technical field, or equivalent work experience</li><li>10+ years of experience in security engineering or related field</li><li>Proven experience defining and executing enterprise security strategy</li><li>Deep knowledge of modern threats, attack techniques, and detection engineering</li><li>Experience with threat modeling, incident response, and security operations</li><li>Demonstrated ability to influence both technical and executive stakeholders</li></ul><h3>Preferred:</h3><ul><li>Experience working with AI/ML systems and security implications</li><li>Knowledge of adversarial AI techniques and AI threat modeling</li><li>Experience with XDR, SIEM, and detection engineering practices</li><li>Familiarity with AI security frameworks (e.g., OWASP LLM Top 10, MITRE ATLAS)</li><li>Financial services industry experience</li></ul><div>&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp;&nbsp;</div><div><strong>Pay Transparency</strong></div><div>Thrivent’s long-term growth depends on attracting, rewarding, and retaining people who are committed to helping others thrive with purpose. We accomplish this by offering a wide variety of market competitive compensation programs to attract, reward, and retain top talent.&nbsp; The applicable salary or hourly wage range for this full-time role is $161,436.00 - $218,415.00 per year, which factors in various geographic regions.&nbsp; The base pay actually offered will be determined by a variety of factors including, but not limited to, location, relevant experience, skills, and knowledge, business needs, market demand, and other factors Thrivent deems important.</div><div><br></div><div>Thrivent is unique in our commitment to helping people to be wise with money and live balanced and generous lives.&nbsp; That extends to our benefits.</div><div><br></div><div>The following benefits may be offered:&nbsp; various bonuses (including, for example, annual or long-term incentives); medical, dental, and vision insurance; health savings account; flexible spending account; 401k; pension; life and accidental death and dismemberment insurance; disability insurance; supplemental protection insurance; 20 days of Paid Time Off each year; Sick and Safe Time; 10 paid company holidays; Volunteer Time Off; paid parental leave; EAP; well-being benefits, and other employee benefits.&nbsp; Eligibility for receipt of these benefits is subject to the applicable plan/policy documents.&nbsp; Thrivent’s plans/policies are subject to change at any time at Thrivent’s discretion.</div>

Principal Engineer - AI Security

<h3>Description</h3><div>The Principal Artificial Intelligence (AI) Software Architect leads the design, development, and deployment of advanced AI and software engineering solutions across the enterprise.&nbsp; This role blends deep expertise in artificial intelligence with architectural leadership in software systems, driving innovation, scalability, and excellence in engineering practices.<br><br></div><div><strong>&nbsp;PRINCIPAL RESPONSIBILITIES AND DUTIES:<br></strong><br></div><ul><li>Architects and leads the development of AI-driven platforms and scalable software systems aligned with strategic business goals.</li><li>Collaborates cross-functionally with engineering, product, and business teams to define use cases and deliver impactful solutions.</li><li>Evaluates and selects AI and software technologies, frameworks, and tools for optimal performance, scalability, and maintainability.</li><li>Establishes and promotes best practices in AI model development, MLOps, software engineering, DevOps, and system architecture.</li><li>Mentors engineering teams, fostering a culture of innovation, excellence, and continuous improvement.</li><li>Drives technical strategy and long-term planning, aligning engineering efforts with enterprise objectives.</li><li>Ensures compliance with data privacy, security, and ethical standards in all AI and software initiatives.</li><li>Champions engineering excellence through code reviews, automated testing, CI/CD, and agile methodologies.</li><li>Other duties as needed or assigned.</li></ul><div><br><strong>SKILLS AND ABILITIES REQUIRED:<br></strong><br></div><ul><li>Hands-on experience driving innovation through emerging technologies and methodologies.</li><li>Excellent communication skills and leadership skills with a track record of mentoring and influencing teams.</li><li>Proven experience designing and deploying AI/ML and software solutions at scale in cloud environments such as Azure, AWS, GCP.</li><li>Expertise in machine learning, deep learning NLP, computer vision, and generative AI.</li><li>Ability to demonstrate strategic thinking and the ability to align technical vision with business objectives.</li><li>Ability to build trust and influence across all levels of the organization, driving consensus and momentum for complex initiatives.</li><li>Advanced knowledge of programming languages within the respective divisions.</li><li>Advanced knowledge of applicable data privacy practices and laws.</li><li>Advanced analytical, conceptual, and problem-solving abilities.</li><li>Advanced level of written and oral communication skills.</li><li>Advanced level of interpersonal and consultative skills.</li><li>Ability to effectively prioritize and execute tasks in a high-pressure environment.</li><li>Ability to work in a team-oriented, collaborative environment.</li></ul><div><br><strong>MINIMUM LEVEL OF PREPARATION AND TRAINING NORMALLY REQUIRED:<br></strong><br></div><ul><li>A bachelor’s degree in the field of computer science, information systems, or computer engineering or equivalent experience.</li><li>7+ years of experience in software architecture and engineering, with at least 2 years focused on AI/ML systems.</li><li>5+ years of hands-on experience with application development tools, including Visual Studio .NET.</li><li>5+ years of hands-on experience with relational database technology, preferably MS SQL Server.</li></ul><div><br></div>

Principal AI Software Architect

<div><strong>Position Summary</strong></div><div><br>Virtuous is evolving its data platform into an AI-ready foundation that powers trusted decision-making and self-service analytics across the company.</div><div><br>We’re hiring a <strong>Lead Data Platform Engineer</strong> to design, build, and <em>own</em> the systems that power our data ecosystem. This role is ideal for a highly motivated self-starter who is comfortable with ambiguity and thrives at the intersection of systems design, business semantics, and AI enablement.</div><div><br>This is <strong>not a traditional data engineering role</strong> focused on building one-off pipelines, dashboards, or ad hoc reports. Success in this role comes from designing and building durable platform capabilities — security models, access patterns, cost controls, and shared data foundations — that enable teams (<em>and AI systems</em>) to safely and confidently use data at scale.</div><div><br>You’ll work closely with the Director of Data Operations as well as our Finance, Product, Engineering and Security Teams to ensure our data platform is accurate, governable, and ready to support AI-enabled workflows across the company.</div><div><strong><br>What You'll Build &amp; Own</strong></div><div><br></div><h3>Data Platform &amp; AI-Enablement</h3><ul><li>Own the evolution of Virtuous’s data platform, primarily on <strong>Snowflake and dbt</strong>, as a secure, scalable, and AI-ready system.</li><li>Design data models, metadata, and access patterns that support <strong>natural-language querying and AI-assisted analysis</strong>.</li><li>Partner with Data Operations and Teams across the company to ensure data structures are accurate, reusable, and aligned with business definitions.</li><li>Prepare data foundations that allow AI tools to deliver consistent, timely, and trustworthy answers.</li><li>Ensure AI systems access data exclusively through governed service accounts and role-scoped permissions, with query activity auditable and restricted according to enterprise data classification and access standards.</li></ul><div><br></div><h3>Access, Trust &amp; Governance by Design</h3><ul><li>Architect and implement role-based access controls within Snowflake and related data systems (including row- and column-level security), ensuring enforcement aligns with enterprise IAM standards, approved access policies, and centralized identity governance processes.</li><li>In partnership with Security Operations and IT, translate approved enterprise access and compliance policies into enforceable platform-level controls, and maintain technical configurations to ensure ongoing alignment with those standards.</li><li>Ensure all platform-level access controls integrate with the enterprise identity provider (SSO, SCIM, role lifecycle management), and support automated provisioning, deprovisioning, and periodic access certification processes.</li><li>Build governance patterns that are enforced by design — not by manual process.</li><li>Support periodic access reviews and control validation processes in coordination with Security and Compliance teams, ensuring appropriate separation of duties between policy definition, approval, and technical implementation.</li></ul><div><br></div><h3>Platform Leverage &amp; Standards</h3><ul><li>Build and maintain <strong>CI/CD pipelines</strong>, testing strategies, and deployment patterns for dbt and Snowflake.</li><li>Design deployment, testing, and validation patterns that make accuracy the default.</li><li>Establish platform standards, templates, and best practices that enable others to move faster without sacrificing quality or security.</li><li>Increase the amount of trusted work the organization can do without increasing Data Ops involvement.</li><li>Reduce ad hoc work by building reusable systems and guardrails.</li><li>Act as a technical leader and thought partner across data-related initiatives.</li></ul><div><br></div><h3>Reliability, Cost &amp; Performance</h3><ul><li>Own Snowflake warehouse strategy, resource governance, and cost optimization.</li><li>Continuously improve performance, scalability, and reliability across the data platform.</li><li>Identify and eliminate inefficiencies that increase cost, risk, or operational overhead.</li><li>Collaborate with IT and Cloud Engineering to ensure Snowflake networking, storage integrations, and data movement patterns align with enterprise cloud security baselines, network segmentation standards, and infrastructure governance policies.</li></ul><div><strong><br>What Success Looks Like</strong></div><ul><li>Teams reliably self-serve data and insights without increasing DataOps workload or risk.</li><li>AI-powered tools consistently answer business questions accurately, using governed data, with access enforced by role and context.</li><li>Data access, governance, and correctness are enforced by platform design rather than manual review or process.</li><li>Platform improvements materially reduce cost, operational risk, or time-to-insight.</li><li>Shared, trusted models replace bespoke datasets and one-off definitions.</li><li>At least one company-critical initiative (e.g., AI enablement, cost optimization, access expansion) succeeds specifically because of systems you designed and built.</li></ul><div><br><strong>Who This Role is For</strong></div><ul><li>Care about leverage, durability, and outcomes — not just shipping artifacts.</li><li>Think deeply about how AI and automation change the role of data platforms.</li><li>Are highly self-directed and motivated, and take pride in ownership.</li><li>Thrive in ambiguity and are comfortable making decisions with incomplete information.</li><li>Are motivated by leverage, correctness, and long-term impact — not ticket volume or titles.</li><li>Readily navigate cross-functional tradeoffs to build shared data foundations that serve the whole company, not individual teams.</li></ul><div><strong><br>You Must Have</strong></div><ul><li>7+ years of experience in data engineering, platform engineering, or related infrastructure roles, with ownership of production systems.</li><li><strong>Deep expertise in Snowflake</strong>, especially:<ul><li>Roles and RBAC</li><li>Row-level and column-level security</li><li>Warehouse design and cost optimization</li><li>Performance tuning and governance</li></ul></li><li><strong>Strong experience using dbt </strong>to build and maintain shared data models, including macro development, testing strategies, source freshness, group model security implementation, and production deployment patterns..</li><li>Advanced SQL skills and experience designing reliable ELT/ETL pipelines.</li><li>Proven systems-thinking mindset, with the ability to reason about tradeoffs across correctness, access, cost, and speed.</li><li>Clear communicator who can explain complex technical concepts to both technical and non-technical partners.</li></ul><div><strong><br>Nice to Have</strong></div><ul><li>dbt certification strongly preferred</li><li>Experience enabling AI/ML or natural-language data access.</li><li>Familiarity with data observability, lineage, or metadata tooling.</li><li>Experience designing platforms for self-service analytics.</li><li>Exposure to BI tools such as Sigma, Looker, or Tableau.</li><li>Experience working in lean, fast-growing organizations where leverage matters more than headcount.</li></ul><div><strong><br>What We Offer</strong></div><ul><li>Market competitive pay leveraging Carta data</li><li>Employee recognition through Bonusly (birthdays, anniversaries, achievements, etc.)</li><li>401(k) retirement plan with company matching- 50% match up to 6% of compensation after 90 days</li><li>We value our employee’s work-life balance and encourage taking advantage of Unlimited PTO</li><li>Supportive time off including paid volunteer days and company holidays</li><li>Employer-contributed healthcare benefits, encompassing medical, dental, and vision coverage, with plans available for dependents and choices for Health Savings Accounts (HSA) and Flexible Spending Accounts (FSA).</li><li>12 weeks primary parent leave, 4 weeks secondary parent leave - full pay (adoption as well)</li><li>We pride ourselves on Community and host exciting company outings and events.</li></ul><div><br><strong>About Us</strong></div><div><br>Virtuous is on a mission to inspire global generosity by helping nonprofits build better relationships with their donors. We offer a modern software platform that provides mid-sized charities with elegant tools for fundraising, marketing, volunteerism, and online giving.</div><div><br>Our talented team is driven to disrupt the status quo in the nonprofit sector. We are hungry, humble, and committed to delivering best-in-class software solutions, customer success interactions, and sales experiences to the world’s leading nonprofits&nbsp;</div><div><br><br></div><div>We also recognize the importance of giving back and making a difference in the communities where we live and work. That's why we practice radical generosity by volunteering at nonprofits or going the extra mile for our team and the customers we serve. We take our work seriously, but we don’t take ourselves too seriously. We believe that life is too short not to love what you do.&nbsp;</div><div><br>The ideal candidate for Virtuous embodies our values by:</div><ul><li>Asking questions with a spirit of curiosity</li><li>Giving feedback freely with candor &amp; grace, welcoming it in return</li><li>Displaying a passion for philanthropy and technology&nbsp;</li><li>Serving with joy. Everyone is willing to make the coffee!</li><li>Celebrating the wins &amp; milestones of others&nbsp;</li><li>Assuming good intent &amp; demonstrating trust in others&nbsp;</li><li>Pursuing relationships with people different from themselves &amp; creates space to be human</li></ul>

Lead Data Platform Engineer

<h3><strong>AI Engineer / Data Engineer&nbsp;</strong></h3><div>Minneapolis, MN Hybrid position <br>Salary: Base salary + bonus + eligible for equity <br><br><strong>Looking For:&nbsp;</strong></div><ul><li>1–5 years of experience as an AI Engineer, ML Engineer, Data Scientist, or Software Engineer with AI/LLM focus.</li><li>Practical experience with LangChain, LlamaIndex, AutoGen, or similar frameworks.&nbsp;</li><li>Experience with prompt engineering.&nbsp;</li><li>Familiarity with vector databases (Pinecone, Weaviate, FAISS, Milvus).&nbsp;</li><li>Experience with cloud platforms like GCP and ML infrastructure tools for AI deployment. &nbsp;</li><li>Strong collaborator and communicator who can work across product, engineering, and data teams.</li><li>Proactive, detail-oriented, organized, and self-sufficient, with a self-starter mentality and ownership attitude. &nbsp;</li><li>Works quickly without sacrificing quality to find creative technical solutions.&nbsp;</li><li>Excited to work at a fast-paced, scaling organization building cutting-edge healthcare technology.&nbsp;</li></ul><div><br></div><div><strong>Great to Have:</strong>&nbsp;</div><ul><li>Retrieval-Augmented Generation experience.&nbsp;</li><li>Proficiency in coding/programming experience (python, node.js) as well as exposure to full-stack integration.&nbsp;</li><li>MLOps/LLMOps/NLP model evaluation, deployment, and monitoring performance metrics.&nbsp;</li><li>Practice with experimentation techniques.&nbsp;</li><li>Proficiency in data manipulation and analysis using tools like pandas, NumPy, and SQL.&nbsp;</li></ul><div><br></div><div><strong>Blow Us Away:</strong>&nbsp;</div><ul><li>Experience with B2B software products.&nbsp;</li><li>Growth-stage company experience.&nbsp;</li><li>Healthcare experience.&nbsp;</li><li>Notable experience in a world-class product offering featuring AI.&nbsp;</li></ul>

AI Engineer / Data Engineer

<div>This role is based out of our Kansas City, Missouri office location to work primarily on site 4 days per week. We are also open to a remote hire based within the U.S. <br><br>You can also apply to our <a href="https://www.paycomonline.net/v4/ats/web.php/jobs/ViewJobDetails?job=87285&amp;clientkey=92484D04B4BA2DDA7D390926D0E49CF2">GO Posting!</a><br><br></div><div><strong>Organizational Profile: &nbsp;</strong></div><div>Are you a technically gifted Data Engineer who wants to use your technical expertise to help transform the lives of children and families? The Global Orphan Project (GO Project) is looking for an experienced and mission-aligned Data Engineer to join our team in Kansas City, MO. We’re a Christian nonprofit ministry dedicated to breaking the orphan cycle through community, commerce, and the love of Jesus Christ. In this pivotal role, you will be the architect behind the systems that power our data strategy—building the pipelines, infrastructure, and governance needed to drive responsible innovation and real-time decision-making in support of children and families in crisis.&nbsp;</div><div>&nbsp;&nbsp;</div><div><strong>Candidate Profile / How Colleagues Describe You: &nbsp;</strong></div><ul><li>Technically Proficient &amp; Detail-Oriented: You thrive on solving complex data challenges and building reliable infrastructure that supports organizational growth.&nbsp;</li><li>Mission-Driven: You’re motivated both by technical excellence and purpose, believing in using data to serve a higher calling.&nbsp;</li><li>Collaborative &amp; Curious: You work well with others, thrive in cross-functional teams, and are always eager to learn from all corners of the organization.&nbsp;</li><li>Governance-Minded: You bring a strong ethical approach to data use, prioritizing security, compliance, and long-term sustainability.&nbsp;</li><li>Adaptable &amp; Inquisitive: You’re quick to learn new technologies and eager to explore innovative tools such as GenAI, LLMs, and data orchestration platforms. &nbsp;</li></ul><div><br></div><div><strong>What You’ll Do: &nbsp;</strong></div><div>As GO Project’s Data Engineer, you’ll be the architect and maintainer of the systems that power our analytics, AI tools, and impact dashboards. Your work will enable better decision-making, faster innovation, and deeper insights across the organization.&nbsp;</div><div>Data pipeline ownership:&nbsp; &nbsp;</div><ul><li>Development, maintenance, testing and optimization of data pipelines across a variety of organizational data-sources (e.g. CRM, product, marketing, donors, etc).&nbsp;</li><li>Coordination with data owners across organization to understand, clean, validate and transform data ready for use in production BI/ML/GenAI applications&nbsp;</li><li>Ensure data pipeline test automation in place catching issues before production&nbsp;</li><li>Partner closely with BI dashboard developers and Data Scientists to ensure clear understanding of data needs&nbsp;</li></ul><div>Data Governance &amp; Quality&nbsp;</div><ul><li>Implement and enforce data governance policies to maintain data quality, consistency, and compliance with applicable regulations.&nbsp;</li><li>Establish and monitor data standards, processes, and best practices to support data quality needs.&nbsp;</li><li>Partner with data owners to continuously improve data quality&nbsp;</li><li>Manage data role-based access systems&nbsp;</li><li>Ensure clear data lineage, data catalogs, data definitions and minimize data duplication across applications&nbsp;</li></ul><div>Data Intelligence Platform, Cloud &amp; LLM Mesh Administration&nbsp;</div><ul><li>Own the architecture and configuration of data intelligence platforms (e.g. Dataiku, DataBricks, etc)&nbsp;</li><li>Establish proper best practices and naming conventions&nbsp;</li><li>Manage data-related cloud technology configurations&nbsp;</li><li>Administer LLM model provider access, APIKeys and licensing&nbsp;</li></ul><div>ML/GenAI Application Deployment &amp; Monitoring&nbsp;</div><ul><li>Understand and utilize MLOps and other monitoring tools to ensure performance standards are met, model drift minimized, etc&nbsp;</li><li>Manage production deployment of ML models, LLMs, and other AI tooling&nbsp;</li></ul><div><strong>Qualifications:<br>&nbsp;</strong>Required Knowledge, Skills &amp; Abilities You Bring to the Organization: &nbsp;<br><br>Education Required: &nbsp;</div><ul><li>Bachelor’s degree in Computer Science, Engineering, Data Science, or a related field.&nbsp;</li></ul><div>Experience:&nbsp;</div><ul><li>3+ years of experience as a Data Engineer or in a comparable technical role.&nbsp;</li><li>Proficient in SQL, Python, and other data programming approaches.&nbsp;</li><li>Fluent with various types of databases (e.g. mySQL, Dynamo, etc), warehouses (e.g. BigQuery, DeltaLake, etc), and analytical systems (e.g. Dataiku, DataBricks, etc).&nbsp;</li><li>Hands-on experience with APIs, ETL/ELT processes, and data integration from diverse systems.&nbsp;</li></ul><div><strong>Preferred:&nbsp;</strong></div><ul><li>Familiarity with data orchestration platforms (e.g., Airflow, dbt, spark, or similar).&nbsp;</li><li>Exposure to GenAI infrastructure (e.g., RAG, vector databases, LLM model types) and production level AI applications&nbsp;</li><li>Cross organization collaboration and “data culture” building&nbsp;</li><li>Close partnerships with data owners and strong business intuition&nbsp;</li></ul><div>Physical Requirements: &nbsp;<br><br>This role is primarily sedentary, with occasional requirements to lift materials up to 15 pounds, such as tech equipment or supplies. &nbsp;<br><br>Why Join Us?&nbsp;<br>At The Global Orphan Project, your expertise will fuel a global mission. You’ll work alongside passionate teammates who care deeply about vulnerable children and families. You’ll help build systems that inform strategy, automate processes, and expand our capacity to serve, while growing personally and professionally.&nbsp;<br><br>We offer a competitive benefits package for full-time roles (30+ hours/week), including health, dental, vision, employer-paid life insurance, 401(k), and generous PTO. You’ll work alongside a talented, value-driven team committed to excellence, innovation, and faith.&nbsp;<br><br>Ready to Build Something that Matters? &nbsp;<br>If you’re excited about using your engineering skills to power a mission-driven organization, we invite you to apply. Submit your resume and a cover letter sharing why you’re a fit for this role and how your faith and expertise align with the GO Project mission. Let’s build a data-driven future that honors families, uplifts communities, and reflects the heart of Christ.&nbsp;</div>

Data Engineer

<div><strong>Job Location:</strong>&nbsp;</div><ul><li>Hybrid in Sewickley, PA</li><li>Hybrid in Palo Alto, CA</li></ul><div><strong><br>Join Us at Gloo: Help Us Build the Leading Technology Platform to Serve the Faith Ecosystem.&nbsp;</strong></div><div><br>At Gloo, we believe relationships catalyze growth—and when technology serves relationships, the world can be transformed, one life at a time.&nbsp; We recognize the faith ecosystem is broad and diverse. It includes churches, parachurch ministries and thousands of non-faith based organizations committed to advancing the flourishing of people. Our purpose is simple yet profound: to shape technology as a force for good, so that people can flourish and communities can thrive.. Therefore, our mission is to build the leading technology platform to serve the faith ecosystem.<br><br></div><div>We are a mission-driven organization, guided by four core principles:<br><br></div><ul><li><strong>Shape Technology for Good:</strong> Whether it’s AI tools, dashboards, or communication tools, we empower leaders with values-aligned solutions that amplify their missional impact with tools they can trust.</li><li><strong>Serve Those Who Serve:</strong> From pastors and donors to network leaders and content creators—we’re passionate about providing technology that helps them do more of what they are called to do.&nbsp;</li><li><strong>Release Collective Strength:</strong> We connect the diverse faith ecosystem—churches, parachurch ministries and thousands of non-faith based organizations committed to advancing the flourishing of people—so they can achieve more together than they could alone.</li><li><strong>Enable Ecosystem Trust:</strong> Trust is the foundation of a connected faith community. We enable transparency, digital rights management, and simplicity to foster confident collaboration.</li></ul><div><br>We are looking for talented, mission-driven individuals to join our team as we create innovative technology solutions that inspire and empower people to release the passion in every person, including you, to be all they were created to be. If you’re ready to make an impact with your talents and skills toward this purpose, we’d love to hear from you!<br><br></div><div><strong>The Opportunity:<br></strong><br></div><div>Join Gloo’s AI Research &amp; Data Science team and turn frontier LLM research into evidence-backed product decisions that help people grow. You’ll own the end-to-end experimentation loop—from designing causal tests and faith-aligned evaluation metrics to automating dashboards that keep model quality, bias, and cost in check. Pastors, parents, and everyday seekers will trust the insights we deliver because you’ll make sure the data behind them is rock-solid.</div><div><br>Your day-to-day blends hands-on analytics with strategic impact:<br><br></div><ul><li><strong>Morning:</strong> run a power analysis on yesterday’s live-traffic experiment, then pull terabytes of telemetry from Snowflake to fine-tune a hallucination detector in PyTorch.</li><li><strong>Mid-day:</strong> pair with an ML engineer to wire your new “faith-alignment” score into the CI pipeline so every model checkpoint is auto-graded before it hits staging.</li><li><strong>Afternoon:</strong> present a causal-impact report to product and design, translating statistical nuance into a clear go/no-go decision for next week’s launch.</li></ul><div><br>You won’t do it alone. You’ll collaborate daily with research scientists, backend engineers, PMs, and Design who care as deeply about human flourishing as they do about clean code. Together you’ll ship world-class eval suites, trusted data pipelines, and self-service insights that let others build on our work.</div><div><br>If you’re ready to trade big-tech bureaucracy for autonomy, mission, and the chance to invent what doesn’t exist yet, we’d love to meet you. This hybrid role is based in Pittsburgh, PA or Palo Alto, CA, with quarterly summits in Boulder and the freedom to see your ideas move from prototype to production—fast.<br><br></div><div><strong>What You’ll Do:<br></strong><br></div><h3><strong>Research &amp; Technical Excellence</strong></h3><ul><li><strong>Design gold-standard evaluation pipelines.</strong> Build offline + online test harnesses that quantify accuracy, hallucination, bias, latency, cost, and <em>faith alignment</em> for every new model checkpoint—then light them up in CI so bad pushes never reach staging.</li><li><strong>Invent metrics that matter.</strong> Translate “human flourishing” into measurable signals (e.g., uplift scores, pastoral-fit indices) and validate them with causal inference, inter-rater reliability, and power analyses.</li><li><strong>Champion testability at data scale.</strong> Instrument data pipelines to emit lineage, privacy flags, and drift stats; automate regression and shadow-traffic tests so research moves fast without breaking trust.</li><li><strong>Advance the craft.</strong> Publish internal whitepapers, run journal clubs on causal ML and LLM evaluation, and mentor engineers in statistical thinking and experiment design.</li></ul><div><br></div><h3><strong>Delivery</strong></h3><ul><li><strong>Ship decision-ready insights.</strong> Own the end-to-end loop—from query in Snowflake or Weaviate, through feature engineering in PyTorch, to a Looker dashboard or Slack bot that PMs use daily.</li><li><strong>Accelerate cycles, not risk.</strong> Template experiment frameworks (A/B, switchback, Bayesian bandits) so product teams can launch tests in hours; automate cleanup, analysis, and “stop/keep/scale” recommendations.<br><strong>Raise the performance ceiling.</strong> Hunt bottlenecks—slow ETL, expensive inference, noisy labels—and knock them down with better schemas, caching, or active-learning pipelines.</li></ul><div><br></div><h3><strong>Strategic Clarity</strong></h3><ul><li><strong>Align analytics with mission.</strong> Partner with product and research to frame how new metrics, datasets, or safety guardrails power coaching, discipleship, and broader human-flourishing outcomes.</li><li><strong>Model trade-offs.</strong> Quantify the ROI of additional GPU spend, bigger context windows, or stricter privacy filters, then brief execs with clear “yes / later / never” options.</li><li><strong>Codify best practice.</strong> Keep living docs on metrics definitions, experiment checklists, and data-governance rules so every team can self-serve without reinventing the wheel.</li></ul><div><br></div><h3><strong>Collaboration</strong></h3><ul><li><strong>Default to cross-functional.</strong> Pair with infra on scalable data stores, with security on PII governance, and with UX on in-product instrumentation that captures the right events the first time.</li><li><strong>Create productive tension.</strong> Ask the hard statistical questions early, surface risks, and drive “disagree-and-commit” clarity so launches stay both fast <strong>and</strong> safe.</li></ul><div><br></div><h3><strong>Leadership &amp; Influence</strong></h3><ul><li><strong>Mentor over manage.</strong> Coach junior analysts and engineers; review code, notebooks, and dashboards to raise the team’s statistical bar.</li><li><strong>Lead from the data.</strong> When the numbers disagree with intuition, speak up—candidly but constructively—then rally the group around evidence-based solutions.</li><li><strong>Institutionalize learning.</strong> Run retros on every major experiment, celebrate lessons (wins or fails), and bake micro-improvements into the next cycle.</li></ul><div><strong><br>In short:</strong> you’ll turn terabytes of raw signals into trustworthy metrics, experiments, and narratives that keep our AI honest and our mission on track—ensuring every insight we ship genuinely helps someone flourish.<br><br></div><div><strong>What We Are Looking For:</strong></div><ul><li>Advanced degree or demonstrable equivalent (peer-reviewed research or high-impact data-science products). &nbsp;</li><li>5+ years in product or research data-science roles designing experiments and shipping insights. &nbsp;</li><li>Expert SQL and Python (Pandas, NumPy); own end-to-end ETL → analysis → dashboard. &nbsp;</li><li>Deep fluency in causal inference, A/B and switchback testing, and metric design. &nbsp;</li><li>Proven ability to evaluate or partner on large-model analytics; familiarity with LLM eval best practices. &nbsp;</li><li>Skilled communicator who turns statistical nuance into decisive recommendations.</li></ul><div><br></div><h3><strong>Preferred Qualifications</strong></h3><ul><li>Hands-on LLM evaluation or bias-audit work; prompt analysis tooling. &nbsp;</li><li>Modern MLOps familiarity (Ray, Airflow, Kubernetes) and GPU cost telemetry. &nbsp;</li><li>Publications at NeurIPS/ICML/KDD or open-source repos &gt; 500 stars. &nbsp;</li><li>Prior work in mission-driven or faith-aligned settings.</li></ul><div><strong><br>Compensation:&nbsp;</strong></div><ul><li>Sewickley, PA - $125,000 - $175,000&nbsp;</li><li>Palo Alto, CA - $175,000 - $225,000</li></ul><div><strong><br>Our Team Members Enjoy:</strong><br>Competitive compensation and discretionary performance bonus commensurate with experience<br><br></div><ul><li>Flexible PTO policy and state-compliant sick leave to support your well-being</li><li>Medical, Dental, and Vision plans with up to 90% coverage for employees</li><li>Generous employer HSA contributions for HDHP elections</li><li>Employer-sponsored 401k program with a 2% employer match</li><li>Learning &amp; Development stipend available after 6 months of employment</li><li>Paid Parental Leave</li><li>A dynamic, talented team, dedicated to changing the world and building an incredible business</li><li>Onsite and virtual social events to keep us connected in our hybrid work environment</li></ul><div><br>Applicants must be currently authorized to work in the United States on a full-time basis. At this time, Gloo is only able to consider candidates who are U.S. Citizens or U.S. Permanent Residents.</div><div><br>Gloo is committed to providing an inclusive and accessible experience for all candidates. If you require a reasonable accommodation during the application or interview process, please contact us at recruiting@gloo.us to let us know how we can support you.</div>

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