Staff Product Engineer (Full Stack)
New
C
CopilotIQ + BiofourmisHealth tech
US-basedFull-TimeStaff
Salary not disclosed
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Job Details
- Experience
- 10+ years of professional software development experience
- Required Skills
- AWSDockerKubernetesMongoDBGoRedisReact
Requirements
- Bring 10+ years of professional software development experience, including substantial experience designing, building, and operating cloud-based production systems end to end.
- Demonstrate a record of setting technical direction as an individual contributor for one or more teams, including architecture decisions and their outcomes.
- Have deep system design experience across services, APIs, data models, event-driven workflows, and third-party integrations, including failure, scale, and cost considerations.
- Have hands-on experience adopting AI coding agents on a production codebase and establishing guardrails with measured effects on quality and speed.
- Have shipped LLM-powered features using frontier models and operated them with evaluations and fallback behavior.
- Have experience with prompt and context management, versioned prompts, retries, timeouts, fallbacks, and logging that protects sensitive data.
- Have experience securing sensitive data through access controls, encryption, and audit logging.
- Have experience in a startup or similarly fast-moving environment with broad engineering ownership.
- Hold a bachelor’s degree in Computer Science or a related technical field, or have equivalent practical experience.
- Be strong across the stack, with deeper expertise in at least one area; the core stack includes React, Go or Java with Spring Boot (or a comparable backend language and framework), AWS, MongoDB and Redis (or comparable data stores), Docker, and Kubernetes.
- Have experience with infrastructure as code, observability tooling, LLM provider APIs, AI coding agents, automated tests, typed interfaces, static analysis, and CI quality gates.
Responsibilities
- Own pod architecture, lead design reviews, and make build, buy, and integration decisions.
- Shape shared services, data models, integration patterns, and platform capabilities across pods.
- Write production code, tackle difficult technical problems, and ship alongside the team.
- Work with Sales, Clinical, and Operations stakeholders to translate workflows and business problems into technical strategy and sequenced plans.
- Partner with product and engineering managers on quarterly goals, outcome metrics, roadmap tradeoffs, and prioritization.
- Define practices and guardrails for AI coding agents, including instructions, acceptance criteria, testing, CI quality gates, and review standards.
- Lead the design and production operation of AI-powered features, including model selection, evaluations, fallbacks, and quality monitoring.
- Set reliability and safety practices, including service-level objectives, observability, incident response, audit trails, feature flags, and data accuracy.
- Lead complex initiatives spanning systems, integrations, data flows, and platform migrations from design through rollout.
- Mentor engineers through design feedback and code review, and communicate technical strategy, tradeoffs, and risks.
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