AI Engineering Lead at AIOS — Remote, $200-$400k/yr + equity
$200k - $400k • Remote • Remote • FullTime
Posted 2mo ago
Job Location
Remote
Tech Stack
Remote Work Policy
Fully remote
Employment Type
FullTime
Categories
Applied AI Engineer
About the job
AIOS is seeking an AI Engineering Lead to build and own the AIOS Agent SDK, which will serve as the foundation for world-class AI agents across the company. This role is not about discovering new AI use cases but about architecting and developing a robust, reusable platform for existing and future agentic workflows. You will be responsible for separating reusable components from specific logic, creating a strongly opinionated internal platform that powers customer-facing agents and AI clinical decision-support systems. The goal is to enable product engineers to build excellent agents efficiently, ensuring they are capable, predictable, safe, and cost-effective. This is a technical leadership position focused on driving innovation and ensuring AIOS is an industry leader in applied AI for production healthcare.
Responsibilities
- Build and own the AIOS Agent SDK as a strongly opinionated internal platform.
- Separate reusable foundations from customer-support logic for the SDK.
- Serve as the DRI for agent architecture, model strategy, evals, AI reliability, and technical safety.
- Ensure product engineers can build agents without recreating core infrastructure.
- Make agents more capable without sacrificing predictability.
- Support major changes with trustworthy evidence across quality, reliability, safety, latency, and cost.
- Strengthen evals, architecture, and models based on production failures.
- Lead by example and grow the AI team.
- Turn Jesse's existing harness into the platform powering Jesse, Aegis, and future agents.
- Own the architecture, reusable primitives, extension points, developer experience, and infrastructure integration of the SDK.
- Become the senior technical owner of Jesse and work closely with the Aegis team.
- Improve Jesse and Aegis by extracting shared foundations.
- Build trustworthy benchmarks using various evaluation methods.
- Establish the path from offline evaluation to controlled production experiments.
- Turn production data (traces, failures, successes) into improved evals, architecture, models, and platform capabilities.
- Make consequential agent actions safe through authorization, validation, and recovery mechanisms.
- Encode compliance, privacy, security, and regional requirements into the platform.
- Own model selection, routing, fallbacks, caching, and manage monthly model spend.
- Lead data preparation, fine-tuning, evaluation, and deployment of specialized open-weight models when supported by evidence.
Requirements
- Technical leadership experience.
- Experience growing a team.
- Experience with agent architecture, model strategy, and AI reliability.
- Experience with AI safety and technical safety.
- Experience with production AI systems in healthcare.
- Experience with building and managing AI infrastructure.
- Experience with model selection, routing, and cost management.
- Experience with fine-tuning and deploying AI models.
- Ability to make autonomous decisions.
- Ability to build trust and set direction for engineers.
Benefits
- Equity
- Full-time, fully remote role
- Work async in timezone of choice
- Regular availability until midday Pacific Time required for collaboration