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# AI Developer Relations Engineer

- **Company:** Felix Technologies Inc.
- **Location:** Seattle, WA, United States
- **Salary:** $193,000.0
- **Contract:** Permanent contract
- **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Application Frameworks, Computing Platforms, User Authentication, Code Review, Cyber Security, Continuous Integration, Data Security, Software Debugging, Python (Programming Language), OpenAI, SQL Databases, Management of Software Versions, Retrieval-Augmented Generation, Large Language Models, Git, Gsuite, Virtual Agents, Automation Anywhere
- **Published:** November 7, 2026
- **Apply:** https://www.careerbuilder.com/job-details/ai-developer-relations-engineer-seattle-wa--cd88b59a-14a9-4727-bad0-464b05ec4cbf

## About the Role

Artificial Intelligence (AI), Funding, Startup, Entrepreneurship, Team Building, Artificial Intelligence (AI), Debugging Skills, Follow Through, Mentoring, Security Infrastructure, * Applied AI experience: Hands-on experience building LLM applications, agents or automations for real users, including what failed and how you improved it.

 * Engineering and diagnostics: Strong Python, APIs, authentication, Git, testing and debugging, with practical use of at least one LLM SDK such as OpenAI or Google. You can read logs and traces, isolate failures and create reproducible examples.
 * Agents and evaluations: Experience with tool calling, multi-step workflows, state, structured outputs, human review and failure handling. You can build useful evaluations and explain quality, latency, cost and data safeguards.
 * Teaching: Experience mentoring builders and mixed technical and business audiences through live builds and debugging, with follow-through after training. This is tested in the interview with a live pairing or debugging exercise.
 * Collaboration: You turn ambiguous requests into testable hypotheses, know when to escalate, and close the loop.

Nice to have

 * Practical SQL and CI/CD
 * RAG and vector databases
 * Maintainable starter kits or reusable components you have built
 * Experience supporting operations teams

## Description

We're looking for an Applied AI Engineer to help the AI team and colleagues across Félix get more out of AI in their daily work. You'll build and debug agents and integrations, help colleagues with their own builds, and turn what works into reusable frameworks and learning resources. Success means teams can use AI on their own, solve technical blockers, and keep their AI workflows running day to day.
You will combine hands-on engineering with technical office hours, mentoring and role-specific learning programs. Working with team leads and Internal Talent, you will identify skill gaps, track applied learning and follow through after training. You will develop expertise in Maestro and other approved platforms, partner with the AI Solutions Manager on shared practices, and engage FDE, AI Enterprise, Data, Security and platform specialists when deeper support is needed., * Build support: Build and improve reference agents, tool integrations and workflows with Python, LLM SDKs and APIs. Pair with colleagues to scope practical builds, review code, and debug prompts, retrieval, tool calls, state, permissions and failures. Production systems stay with FDEs and specialist engineers.

 * Office hours and escalation: Run regular technical office hours, triage requests and track issues to closure. Escalate complex integration, data, security or production problems with reproducible examples, logs and attempted fixes, and turn recurring issues into resources.
 * Reusable frameworks: Turn shared standards into starter kits, tested agents, integration patterns and troubleshooting guides, with examples for tool calling, data access, evaluations, human review and failure handling. Keep documentation, versioning, permissions and ownership clear on approved platforms, including Maestro, our in-house AI assistant that works across Slack, Notion, Google Workspace and our data.
 * Technical teaching and mentoring: Own the technical content and exercises for hands-on bootcamps and tracks, and teach through live builds and debugging. Mentor colleagues through guided builds and code reviews until they can maintain their own work.
 * Platform expertise and improvement: Keep working expertise in Maestro, other approved tools and data safeguards. Test new capabilities on real tasks, share practical guidance, and bring recurring gaps to platform owners. Track independent task completion, blocker resolution, resource reuse and sustained adoption.