AI Developer Relations Engineer

Felix Technologies•Seattle, WA

1d•Hybrid

About The Position

Félix is hiring an Applied AI Engineer to help its AI team and colleagues across the company use AI effectively in their daily work. The role combines hands-on engineering with technical office hours, mentoring, and role-specific learning programs. The successful candidate will build and debug agents and integrations, assist colleagues with their projects, and turn successful approaches into reusable frameworks and learning resources so teams can use AI independently and keep their workflows running. The role involves building reference agents, tool integrations, and workflows with Python, LLM SDKs, and APIs; pairing with colleagues to scope builds, review code, and debug technical issues; running office hours and tracking requests through resolution; and escalating complex issues to specialist teams. The engineer will create starter kits, tested agents, integration patterns, and troubleshooting guides, while maintaining clear documentation, versioning, permissions, and ownership on approved platforms, including Maestro. They will also develop and teach technical learning content, mentor colleagues through guided builds and code reviews, test platform capabilities, and work with platform owners to address recurring gaps. Production systems remain with FDEs and specialist engineers.

Requirements

Hands-on experience building LLM applications, agents, or automations for real users, including experience learning from failures and improving the work.
Strong Python, APIs, authentication, Git, testing, and debugging skills.
Practical experience with at least one LLM SDK, such as OpenAI or Google.
Ability to read logs and traces, isolate failures, and create reproducible examples.
Experience with tool calling, multi-step workflows, state, structured outputs, human review, and failure handling.
Ability to build useful evaluations and explain quality, latency, cost, and data safeguards.
Experience mentoring builders and mixed technical and business audiences through live builds and debugging, with follow-through after training.
Ability to turn ambiguous requests into testable hypotheses, identify when to escalate, and close the loop.
Successful completion of a live pairing or debugging exercise during the interview.

Nice To Haves

Practical SQL experience.
CI/CD experience.
Experience with RAG and vector databases.
Experience building maintainable starter kits or reusable components.
Experience supporting operations teams.

Responsibilities

Build and improve reference agents, tool integrations, and workflows using Python, LLM SDKs, and APIs.
Pair with colleagues to scope practical builds, review code, and debug prompts, retrieval, tool calls, state, permissions, and failures.
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.
Turn recurring issues and shared standards into starter kits, tested agents, integration patterns, and troubleshooting guides.
Create examples for tool calling, data access, evaluations, human review, and failure handling.
Maintain clear documentation, versioning, permissions, and ownership on approved platforms, including Maestro.
Own technical content and exercises for hands-on bootcamps and learning tracks, teaching through live builds and debugging.
Mentor colleagues through guided builds and code reviews until they can maintain their own work.
Maintain working expertise in Maestro, other approved tools, and data safeguards.
Test new platform 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.