Staff AI Platform Engineer

Quick Facts

• Role: Staff AI Platform Engineer (AI Platforms)

Description

Own production AI-platform components end to end, setting technical direction and building paved paths that other teams can adopt. You’ll develop the agent runtime and orchestration platform, secure MCP gateway and connectors, LLM gateway (model access/routing, auth, rate limits, token budgets, cost attribution), evals/regression infrastructure, observability, cost controls, and memory/knowledge infrastructure. You’ll ensure security, privacy, and auditability are built in from day one and partner with AI Dev Tooling and Agentic PDLC to turn needs into shared platform primitives.

Responsibilities

• Establish the vision and paved paths for AI-native engineering best practices

• Build agent runtime/orchestration with identity, authorization, and audit for scheduled/unattended agents

• Operate MCP gateway and connector infrastructure with secure, managed, auditable access

• Support the LLM gateway: access/routing, authentication, rate limits, token budgets, per-team cost attribution

• Build eval and regression infrastructure (golden datasets, offline evals, CI hooks, result storage)

• Set up observability (prompt/response tracing, cost per request, quality signals, drift detection)

• Partner with Security/Privacy/Legal for tenant isolation, auditability, and compliant data handling

• Define how product teams run/monitor AI inference in production (serving, latency, reliability, provider management)

• Own production operations (SLOs, dashboards, deployment pipelines, incident response)

• Enable shared memory/retrieval/knowledge infrastructure for agents

• Create developer enablement (SDKs, templates, reusable skills, docs, champions)

• Mentor engineers; write design docs and standards; explore longer-term shared memory/knowledge capabilities

Requirements

• 8+ years of engineering experience; 3+ years building platforms/infrastructure used by other engineers

• Production experience with AI systems such as agentic workflows, LLM integrations, retrieval, and evaluation

• Working knowledge of MCP and agent orchestration with proper controls for connecting agents to internal systems

• Strong backend/cloud fundamentals: distributed systems, APIs, infrastructure as code, reliability and observability

• Experience running AI inference in production with focus on latency, reliability, provider management, and cost tradeoffs

• Sound judgment on where to invest in shared platform capabilities

• Clear written communication via design docs and standards

Benefits

• Medical, dental, vision, life, and disability insurance (100% paid for employees)

• Paid parental leave

• 401(k) with company matching

• Mental Wellness Program and EAP

• Flexible PTO, companywide holidays, plus summer and winter shutdowns

• Learning & Development programs

• Equipment/tools and reimbursement support for remote work

• Free Life360 Platinum Membership and Tile trackers