AI Developer Relations Engineer

Félix

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

Posted 11/5/2026full-timeNew York City • New York • 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, APIs, and LLM SDKs, while effectively mentoring colleagues and maintaining documentation and resources for technical training.

Highest-signal resume keywords

Python ProgrammingLLM Application DevelopmentAPI IntegrationMentoring and TrainingSQL and CI/CD

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

PythonAPIsLLM SDKTestingDebuggingSQLCI/CDTool CallingMulti-Step WorkflowsData Safeguards

Soft Skills

MentoringCollaborationProblem-SolvingCommunicationAdaptability

Tools & Technologies

MaestroOpenAIGoogle LLM SDKRAG DatabasesVector Databases

Industry Keywords

Technical Office HoursIntegration PatternsTroubleshooting GuidesDocumentationData Security

Tech Stack

Tools & technologies

PythonSQL

About the role

Key responsibilities & impact

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
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 into reusable resources
Create 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
Mentor colleagues through guided builds and code reviews
Maintain expertise in Maestro, approved tools and data safeguards
Test new capabilities on real tasks, share guidance, bring recurring gaps to platform owners, and track adoption outcomes
Work with team leads, Internal Talent, AI Solutions, 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
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
RAG and vector databases
Maintainable starter kits or reusable components you have built
Experience supporting operations teams

Benefits

Comp & perks

Competitive salary
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