Senior Staff Applied AI Engineer

OpenLoop is building the future of healthcare infrastructure. We are hiring a Senior Staff Applied AI Engineer to be one of the first technical leaders for AI at OpenLoop. As one of the earliest hires, the decisions you make become the foundation everyone else builds on: how our AI agents run, how we prove they are good, how we keep them safe and affordable, and how other teams build agents on our platform.

Responsibilities

Agent Runtime & Orchestration: Set the technical direction for how agents run, call tools, hold context and hand off work, including failure handling, retries, timeouts and sandboxing; Evaluation: Build the systems that prove AI is actually good, including regression tests and AI-graded evals; Model Access & Operations: Set up access to models from multiple providers, route between them, manage version upgrades and plan fallbacks; Observability & Cost: Trace what agents did and why, monitor behavior in production, and attribute AI spend to each agent and use case with budgets and guardrails; Grounding & Retrieval: Connect agents to real company data and documents through retrieval (RAG), context design and prompt engineering; Workflow Design: Partner with operations teams to turn human workflows into agent workflows; Security, Privacy & Safety: Keep patient data (PHI) protected in every AI system, control what agents can access, and defend against misuse such as prompt injection; Cloud & Data Foundations: Make sound infrastructure decisions on GCP and partner with the Data Platform teams; Technical Leadership: Set and document direction, make build-versus-buy calls, keep the platform general enough for many teams, and mentor engineers new to AI through code and design review; Cross-functional Work: Explain AI trade-offs in plain language to product, operations and clinical stakeholders; Other duties as assigned

Requirements

Bachelor's degree in Computer Science, Engineering, or a related technical field; 12+ years of software engineering experience, with a track record at tech lead, staff or principal-level scope; 2+ years building and running LLM-based systems in production that real users relied on; Deep, hands-on expertise in agent runtime or evaluation, a second area of real depth, and working knowledge across the rest of the AI engineering stack; A track record of measuring AI quality with real evaluation sets and test harnesses, and reporting results with numbers; Experience leading a small team's technical direction from zero, or close to it, in a greenfield setting; Excellent communication skills with the ability to explain complex technical concepts and trade-offs to non-technical stakeholders

Nice to have

Regulated-Industry Experience: Healthcare (PHI, HIPAA), finance or insurance; GCP Experience: Running production services on Google Cloud; Internal Platforms: Built a platform used by other engineering teams; Team Scaling: Helped grow a single pod into multiple teams

Benefits

Medical, Dental, and Vision plans; Flexible Spending/Health Savings Accounts; Flexible PTO; 401(k) + Company Match; Life Insurance, Pet insurance, and more