AI Developer Relations Engineer

Félix

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

Posted 11/5/2026full-timeMiami • Florida • United StatesMid-LevelSenior💰 $164,000 - $182,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates expertise in building and improving LLM applications and integrations using Python and various SDKs, while effectively mentoring colleagues and maintaining comprehensive documentation. Proficient in debugging, collaboration, and transforming complex issues into actionable resources.

Highest-signal resume keywords

Python ProgrammingLLM Application DevelopmentAPI IntegrationMentoring and TrainingDebugging and Troubleshooting

ATS Keywords

Tailor your resume

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills

PythonAPIsGitTestingDebuggingLLM SDKTool CallingMulti-Step WorkflowsData SafeguardsLog Analysis

Soft Skills

CollaborationProblem-SolvingCommunicationMentoringAdaptability

Tools & Technologies

MaestroOpenAI SDKGoogle SDK

Industry Keywords

Integration PatternsTechnical DocumentationUser ExperienceAutomationQuality Evaluation

Tech Stack

Tools & technologies

Python

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 resources, including 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 tracks, teaching through live builds and debugging.
Mentor colleagues through guided builds and code reviews until they can maintain their own work.
Keep working 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, 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, 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.
Collaboration skills: turn ambiguous requests into testable hypotheses, know when to escalate, and close the loop.
This is tested in the interview with a live pairing or debugging exercise.

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