AI Developer Relations Engineer

Felix Technologies•New York, NY

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 help teams use AI independently, resolve technical blockers, and keep AI workflows running day to day. The engineer will develop and debug agents and integrations, support colleagues with their own builds, and turn successful approaches into reusable frameworks and learning resources. The role develops expertise in Maestro and other approved platforms, partners with the AI Solutions Manager on shared practices, and works with FDE, AI Enterprise, Data, Security, and platform specialists when deeper support is needed. Production systems remain the responsibility of FDEs and specialist engineers. Félix describes itself as a hyper-growth Series C company with more than $300 million in funding. Its stated culture emphasizes customer focus, urgency, ownership, ego-free collaboration, transparency, curiosity, and experimentation. The role is hybrid. The starting base salary typically ranges from $193,000 to $213,000 USD, with equity as a core part of total compensation.

Requirements

Hands-on experience building LLM applications, agents, or automations for real users, including 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, know when to escalate, and close the loop.
Must complete 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 through resolution.
Escalate complex integration, data, security, or production problems with reproducible examples, logs, and attempted fixes.
Turn recurring issues into resources and shared standards into starter kits, tested agents, integration patterns, and troubleshooting guides.
Provide examples for tool calling, data access, evaluations, human review, and failure handling.
Maintain documentation, versioning, permissions, and ownership on approved platforms, including Maestro.
Own technical content and exercises for hands-on bootcamps and learning tracks, and teach 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 bring recurring gaps to platform owners.
Track independent task completion, blocker resolution, resource reuse, and sustained adoption.
Work with team leads and Internal Talent to identify skill gaps, track applied learning, and follow through after training.
Partner with the AI Solutions Manager on shared practices and engage FDE, AI Enterprise, Data, Security, and platform specialists when deeper support is needed.