AI Developer Relations Engineer
About The Position
Félix is seeking 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 engineer will build and debug agents and integrations, support colleagues with their own builds, and turn successful practices into reusable frameworks and learning resources. The goal is to help teams work independently with AI, resolve technical blockers, and keep AI workflows running day to day. The role works with team leads and Internal Talent to identify skill gaps, track applied learning, and follow up after training. It develops expertise in Maestro and other approved platforms and partners with the AI Solutions Manager on shared practices. For deeper issues, the engineer engages FDE, AI Enterprise, Data, Security, and platform specialists. Production systems remain the responsibility of FDEs and specialist engineers.
Requirements
- Hands-on experience building LLM applications, agents, or automations for real users, including experience identifying failures and improving solutions.
- 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, recognize when to escalate, and close the loop.
Nice To Haves
- Practical SQL and 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 through resolution.
- Escalate complex integration, data, security, or production problems with reproducible examples, logs, and attempted fixes; turn recurring issues into resources.
- Create starter kits, tested agents, integration patterns, and troubleshooting guides based on shared standards, with examples covering 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 capabilities on real tasks, share practical guidance, and raise recurring gaps with platform owners.
- Track independent task completion, blocker resolution, resource reuse, and sustained adoption.
Benefits
- 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.
- Growth opportunities in a dynamic entrepreneurial environment.
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What This Job Offers
Job Type
Full-time
Education Level
No Education Listed
