Staff Product Engineer – Full Stack

This is a fully remote position, open to applicants in United States.

📋 Description

• Establish the technical direction, oversee system architecture, conduct design reviews, and make decisions regarding build, buy, and integration options.

• Influence architecture across various pods, including shared services, data models, integration patterns, and platform capabilities.

• Develop production code, tackle challenging technical issues, and deliver alongside the team.

• Collaborate with Sales, Clinical, and Operations stakeholders to comprehend workflows and convert business challenges into technical strategies and sequential plans.

• Promote a mobile-first member experience.

• Collaborate with the product manager and engineering managers on quarterly objectives, metrics, roadmap trade-offs, and prioritization.

• Define and enhance team practices for AI coding agents, including guidelines, specifications, acceptance criteria, testing, CI quality gates, and review standards for patient data, clinical logic, and billing modifications.

• Lead the design of AI-powered product features, encompassing model selection, structured outputs, evaluations, fallback strategies, and quality, latency, and cost monitoring.

• Establish reliability and safety benchmarks, including SLOs, observability, incident response, audit trails, feature flags, progressive rollouts, and end-to-end data precision.

• Engage in on-call rotations and incident response activities.

• Direct complex multi-system projects, including third-party integrations, data flows, and platform migrations, from design through implementation.

• Mentor engineers through design feedback and code reviews, and assist in developing pod leads and future Staff engineers.

• Articulate technical strategy, trade-offs, and risks to engineers, stakeholders, and leadership.

⛳️ Requirements

• Extensive experience in building production software across both frontend and backend.

• Proven track record of delivering user-facing features and shaping project scope.

• Ability to communicate clearly with non-engineers and comfort in collaborating directly with internal teams.

• Strong system design capabilities that encompass data modeling, APIs, failure management, observability, reliability, and security by design.

• Regular experience with AI coding assistants, while understanding their limitations.

• Must be US-based due to work involving protected health information.

• 10+ years of professional software development experience, which includes designing, building, and operating cloud-based production systems from start to finish.

• Experience in setting the technical direction as an individual contributor for one or multiple teams.

• In-depth system design experience across services, APIs, data models, event-driven workflows, and third-party integrations.

• Hands-on leadership in adopting AI coding agents within production codebases.

• Experience in shipping and operating LLM-powered features in production, including evaluations and fallback behavior.

• Familiarity with prompt and context management, versioned prompts, retries, timeouts, fallbacks, and privacy-preserving logging.

• Proven experience in securely handling sensitive data, including access controls, encryption, and audit logging.

• Background in a startup or similarly fast-paced environment.

• Bachelor’s degree in Computer Science, a related technical field, or equivalent practical experience.

• Strong frontend and backend experience, with deeper expertise in at least one area.

• Experience with React and production-grade web applications.

• Proficiency in Go, Java with Spring Boot, or a comparable backend language and framework.

• Familiarity with AWS services such as Lambda, SQS, DynamoDB, and API Gateway.

• Experience with MongoDB and Redis or similar data stores.

• Knowledge of Docker and Kubernetes.

• Experience in infrastructure as code using Terraform, AWS CloudFormation, or AWS CDK.

• Familiarity with logging, monitoring, alerting, and observability tools.

• Experience with LLM provider APIs, structured outputs, function calling, tool usage, streaming, rate limits, timeouts, provider errors, evaluation suites, tracing, and production monitoring.

• Experience with AI coding agents such as Claude Code, Cursor, or Codex, as well as automated tests, typed interfaces, static analysis, and CI quality gates.

🏝️ Benefits

• Comprehensive health, dental, and vision insurance.

• Flexible work hours and remote work options.

• Professional development opportunities and ongoing training.

• Generous paid time off and holiday schedule.

• Collaborative and innovative work environment.