Principal AI Engineer, Pair Team

• Systems-Oriented Technical Leader: You think in systems, not features. You make strong architectural decisions, navigate trade-offs effectively, and help shape technical direction across teams
• Applied Agentic AI Builder: You’ve built and scaled production agentic AI systems that perform meaningful work beyond simple chat interfaces. You understand agent behavior, tool orchestration, stateful workflows, and the realities of operating AI systems in production
• Product-Minded Engineer: You work closely with product managers and domain experts to define problems and translate ambiguity into clear technical solutions. You care about outcomes, not just implementation
• Strong Judgment in Ambiguity: You’re comfortable operating in evolving problem spaces, balancing experimentation with reliability and knowing when to prioritize speed versus long-term investment
• Data & Evaluation Driven: You use metrics, evaluation frameworks, and operational feedback to guide decisions and continuously improve system performance
• Highly Autonomous Executor: You take ownership of complex problem spaces end-to-end, balancing speed with engineering rigor and iterating effectively based on real-world feedback
• Multiplying Presence: You elevate those around you — mentoring engineers, establishing best practices, and helping raise the bar for how AI systems are designed and operated
• 8+ years of experience building and shipping production software systems, including experience operating at a Principal IC level and driving technical direction across complex systems
• Proven experience building and scaling multi-agent or agent-driven systems in production and real-world operational ownership (beyond simple chat or LLM workflows)
• Hands-on experience with modern agent ecosystems, including frameworks (e.g., LangGraph, Mastra, Claude Agents SDK), observability/evals tooling (e.g., Langfuse, LangSmith, Braintrust), MCP implementations, and leading AI SDKs (e.g., OpenAI, Anthropic)
• Strong systems and backend architecture fundamentals, with experience designing scalable, reliable systems and handling infrastructure, performance, failure modes, cost, and deployment concerns
• Clear agentic evaluation mindset, including automated evals, simulation-based testing, regression frameworks, metrics design, and continuous improvement loops. Firsthand experience addressing performance and reliability of scaled agentic systems
• AI-native builder with high velocity and ownership, demonstrating intellectual curiosity, rapid adoption of new tools, bias to action, and the ability to drive ambiguous problems from concept to production
• Strong cross-functional collaborator and communicator, able to partner with Product, Operations, and domain experts to deliver end-to-end systems with measurable real-world impact
• Force-multiplier technical leader, raising the bar for clarity of thinking, system design standards, and team execution

Desirable

• As a Principal AI Engineer, you will help design and build the architecture that enables this evolution, translating complex care processes into reliable, production-grade AI systems in close partnership with product and domain experts
• Lead the design and evolution of agentic systems that participate directly in care delivery, helping coordinate care, engage patients, and execute meaningful portions of care workflows
• Define and build architectural patterns for agent reasoning, tool use, memory, and human-in-the-loop collaboration
• Develop both reusable platform capabilities and product-facing implementations, balancing long-term architecture with rapid iteration
• Own complex problem spaces end-to-end — from system design and implementation through observability, evaluation, and continuous improvement in production
• Partner closely with product managers, operators, and domain experts to translate complex real-world processes into reliable agent behavior
• Establish standards and best practices for agent evaluation, safety, and operational reliability as these systems evolve toward greater autonomy
• Mentor engineers and influence technical direction across teams building agent-driven capabilities