Staff AI Engineer
New
M
MoxieAesthetic practice software
Remote - GlobalFull-TimeStaff
Salary97,000 - 225,000 USD per year
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Job Details
- Required Skills
- GraphQLPostgreSQLPythonDjangoRedisRESTful APIs
Requirements
- Have staff-level engineering experience leading large, ambiguous initiatives as a hands-on individual contributor.
- Own delivery, tradeoffs, and major architectural decisions across teams.
- Have led the design and delivery of production LLM agents or generative features used by real customers.
- Have improved engineering practices and influenced peers across teams.
- Work with Product, Design, and engineering leadership to resolve complex decisions and raise engineering standards.
- Have built evaluation systems for production AI using automated tests, agent traces, human feedback, and production monitoring.
- Design safe tool boundaries and human handoffs, and determine when to use deterministic code versus an LLM.
- Manage reliability, security, latency, and cost tradeoffs, including build-versus-buy and model-provider decisions.
- Have backend and platform engineering experience with Python, Django, Postgres, Redis, and async workers.
- Design shared AI infrastructure with clear contracts, caching, and tenant isolation.
- Be comfortable working with REST or GraphQL.
Responsibilities
- Contribute to and lead production AI initiatives, including Maia, AI drafts, and the Context Engine.
- Deliver improvements to known AI failure modes, evaluation coverage, and production reliability.
- Lead AI projects from design and architecture review through cross-functional delivery and launch.
- Build evaluation and guardrail systems to operate AI features reliably.
- Lead technical proposals and influence architectural decisions across teams.
- Own AI architecture and the shared AI platform.
- Establish measurable AI quality scorecards and catch regressions before production.
- Improve shared evaluations, guardrails, and observability for AI systems.
- Own organization-level initiatives such as AI evaluation standards, agentic SDLC improvements, code review practices, or documentation culture.
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