Staff Software Engineer, AI-Native Systems

Wheel; United States; À distance; USD 180 000 - 260 000; Plein temps

Résumé du poste

Wheel builds the infrastructure behind telehealth, delivering AI-native systems at scale in a regulated environment. As a Staff Software Engineer, you will define technical direction for agent architectures, lead squads, and ship measurable outcomes.

You will code hands-on, set production-ready standards, and drive guardrails across teams. This is a remote US role, focused on rebuilding healthcare workflows with observable platforms.

Qualifications

• Staff-level engineer with a track record shipping production AI agents.
• Experience building and operating agents in production in regulated environments.
• Ability to define problems, sequence work, and lead engineers to measurable outcomes.
• Owns technical direction and establishes clear ownership across teams.
• Fluent in designing AI-native architectures with guardrails.

Responsabilités

• Own the technical direction for a significant AI-native domain: agent architecture, platform abstractions, or evaluation and guardrail infrastructure.
• Act as tech lead for a squad or cross-team initiative — decomposing ambiguous problems, sequencing delivery, clearing blockers, keeping the team pointed at the outcome.
• Write and review design docs; document load-bearing architectural calls, including “not yet” or “buy, don’t build.”
• Establish clear technical ownership where it’s currently diffuse to avoid stalled reviews.
• Design and build production AI agents with retrieval, orchestration, policy-based routing, tool invocation, evaluation harnesses, and lifecycle observability.
• Set standards for what constitutes a production-ready agent: testability, rollback safety, cost ceilings, failure modes, human-in-the-loop boundaries.
• Take on the hardest parts of the build hands-on and stay in the code.
• Build and extend abstraction layers to let teams integrate AI safely across services.
• Define shared libraries and patterns for safe AI integration across the platform.

Connaissances

Technical leadership

Agent architecture

Production systems

Design docs

Cross-team leadership

Regulated environment

Description du poste

Staff Software Engineer, AI-Native Systems (Tech Lead)

Location: Remote (US)

We are

Virtual care only works if the infrastructure behind it does. Wheel builds that infrastructure — the systems that let telehealth run at scale for the patients, clinicians, and companies depending on it. We're not bolting AI onto old workflows; we're rebuilding them from the ground up. Our mission to put great healthcare in everyone's reach means replacing manual, ad-hoc processes with intelligent, agent-powered systems that carry real operational load. We're innovating in a live, regulated healthcare environment where getting it right matters. This is the next architecture of virtual care, and we're building it now.

You are

A staff-level engineer who sets technical direction for agentic systems and then leads the work to ship them. You've built and operated agents in production, you know where they break, and you have opinions — held loosely, argued well — about how to build them so they hold up in a regulated environment.

You operate with the scope of a domain owner, not a task owner. You take a problem that isn't yet well-formed, define it, sequence it, and lead a group of engineers to a shipped and measured outcome. Your impact shows up in other people's work as much as your own: the patterns they reuse, the design decisions they don't have to relitigate, the ambiguity you removed before it cost the team a quarter.

You treat AI two ways at once — as a product capability you build with judgment, and as a development multiplier you use fluently — and you're the person who raises the org's bar on both.

The Work

Technical Leadership Direction

• Own the technical direction for a significant AI-native domain: agent architecture, platform abstractions, or evaluation and guardrail infrastructure.
• Act as tech lead for a squad or a cross-team initiative — decomposing ambiguous problems, sequencing delivery, identifying and clearing blockers, and keeping the team pointed at the outcome rather than the ticket.
• Write and review design docs; make and document the load-bearing architectural calls, including the ones where the answer is "not yet" or "buy, don't build."
• Establish clear technical ownership where it's currently diffuse, so decisions have a named owner and reviews don't stall.

Agent Architecture Engineering

• Design and build production AI agents incorporating retrieval, orchestration, policy-based routing, tool invocation, evaluation harnesses, and lifecycle observability.
• Set the standards for what "production-ready agent" means here — testability, rollback safety, cost ceilings, failure modes, human-in-the-loop boundaries — and hold the bar in review.
• Take on the hardest parts of the build yourself. This is a hands-on role; you are expected to be in the code.

AI Platform Foundations

• Build and extend the abstraction layers that let teams integrate AI capabilities cleanly and safely across our services.
• Define the shared libraries, patter