Senior Engineering Manager, AI Platform

OpenLoop Health•Des Moines, IA

About The Position

OpenLoop is hiring a Senior Engineering Manager to build and lead its Applied AI team, which develops LLM-based agents and assistants used by operations, clinical, and patient-facing teams. This leadership role combines people management with technical depth. The manager will hire and develop Senior, Staff, and Senior Staff Applied AI Engineers; own delivery and operation of production AI systems; and set standards for building, evaluating, and safely running AI systems that handle patient data. The role does not require writing production code daily, but does require credibility in architecture and evaluation reviews.

Requirements

Bachelor's degree in Computer Science, Engineering, or a related technical field.
10+ years of software engineering experience, including 3+ years directly managing engineers, with responsibility for hiring, performance management, and career development.
Experience leading or building production LLM-based systems relied on by real users, rather than only demos, prototypes, or personal projects.
Experience managing senior and Staff-level engineers and earning their technical trust.
Working understanding of agent runtime, evaluation, retrieval, and observability sufficient to review designs, challenge assumptions, and make sound architecture decisions.
Commitment to measuring AI system performance with evaluation data.
Strong production engineering grounding across testing, services, APIs, deployment, incident management, and on-call.
Experience leading teams that handle sensitive data with a security-first mindset.
Comfort working in a greenfield space and communicating clearly with technical and non-technical partners.

Nice To Haves

Experience in a regulated industry such as healthcare (PHI, HIPAA), finance, or insurance.
Experience leading teams that run production services on Google Cloud (GCP).
Experience growing an engineering team from zero or from one team to several.
Experience leading migrations between model versions or providers.
Machine learning experience beyond LLMs.
Experience leading an internal platform used by other engineering teams.

Responsibilities

Hire, onboard, and develop Applied AI Engineers at Senior, Staff, and Senior Staff levels, and grow the team from one pod into multiple teams as work expands.
Drive the roadmap and execution of production LLM-based agents and assistants, from scoping and launch through ongoing operation.
Partner with Staff+ engineers on architecture for agent runtime and orchestration, retrieval, model access, and observability; make technical trade-off decisions.
Establish evaluation sets, regression tests, and AI-graded evaluations as required parts of the team's shipping process.
Own the operational health of production AI systems, including on-call, incident response, provider fallbacks, model version upgrades, and AI spend by agent and use case.
Ensure AI systems protect patient data (PHI), use least-privilege access, and defend against misuse such as prompt injection; partner with Security and Compliance on HIPAA requirements.
Work with Product and Operations leaders to identify workflows suitable for agents, determine when agents should hand off to people, and prioritize use cases.
Communicate AI capabilities, risks, and timelines clearly to product, operations, clinical, and executive stakeholders.
Run planning, prioritization, and delivery rituals; provide clear feedback and build career paths while supporting team health.