AI Developer Relations Engineer

Félix

. Build and improve reference agents, tool integrations and workflows using Python, LLM SDKs and APIs.

Posted 11/5/2026full-timeSeattle • Washington • United StatesMid-LevelSenior💰 $193,000 - $213,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in building and improving LLM applications and integrations using Python and APIs, while effectively mentoring colleagues and managing technical content for training. Proficient in debugging, documentation, and maintaining data safeguards across approved platforms.

Highest-signal resume keywords

Python ProgrammingLLM Application DevelopmentAPI IntegrationDebugging and TestingMentoring and Training

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

PythonAPIsGitSQLCI/CDLLM SDKDebuggingTestingTool CallingMulti-Step Workflows

Soft Skills

MentoringCollaborationProblem-SolvingCommunicationAdaptability

Tools & Technologies

MaestroOpenAIGoogle LLM SDKRAG DatabasesVector Databases

Industry Keywords

Data SafeguardsTechnical DocumentationIntegration PatternsTroubleshooting GuidesOperational Support

Tech Stack

Tools & technologies

PythonSQL

About the role

Key responsibilities & impact

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.
Maintain documentation, versioning, permissions and ownership on approved platforms including Maestro.
Own technical content and exercises for hands-on bootcamps and learning tracks.
Teach through live builds and debugging, and mentor colleagues through guided builds and code reviews.
Maintain expertise in Maestro, approved tools and data safeguards; test new capabilities and share practical guidance.
Track independent task completion, blocker resolution, resource reuse and sustained adoption.
Partner with team leads, Internal Talent, the AI Solutions Manager, FDE, AI Enterprise, Data, Security and platform specialists.

Requirements

What you’ll need

Hands-on experience building LLM applications, agents or automations for real users, including what failed and how you improved it.
Strong Python, APIs, authentication, Git, testing and debugging, with practical use of 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, know when to escalate, and close the loop.
Practical SQL and CI/CD (nice to have).
RAG and vector databases (nice to have).
Maintainable starter kits or reusable components built (nice to have).
Experience supporting operations teams (nice to have).

Benefits

Comp & perks

Initial stock options grant
Annual performance bonus
Unlimited PTO
Paid parental leave
Hybrid work setup
401(k) with employer matching, for US-based employees
Health, dental, and vision plans
Continuous learning opportunities
Empowering opportunities for growth in a dynamic entrepreneurial environment