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Open nowPosted 8 days ago

Senior Product Engineer (Full Stack)

CopilotIQ9 open roles

Where
Remote
Work mode
Remote
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Your applicationOpen nowSenior Product Engineer (Full Stack)CopilotIQ · Remote

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The clock on this job

Early applications get read.

13.8% of postings close within 7 days. Measured by our own scanner across the market. CopilotIQ postings stay open a median of 51 days.

Share of postings closed within
  1. 2.2%1 day
  2. 4.7%3 days
  3. 13.8%7 days
  4. 22.3%14 days
  5. 37.8%30 days
  6. 59.0%60 days
This job: posted 8 days ago

CopilotIQ median: 51 days open

The posting

At the forefront of health tech innovation, CopilotIQ+Biofourmis is transforming in-home care with the industry's first AI-driven platform that supports individuals through every stage of their health journey-from pre-surgical optimization to acute, post-acute and chronic care. We are helping people live healthier, longer lives by bringing personalized, proactive care directly into their homes. With CopilotIQ's commitment to enhancing the lives of seniors with chronic conditions and Biofourmis' advanced data-driven insights and virtual care solutions, we're setting a new standard in accessible healthcare. If you're passionate about driving real change in healthcare, join the CopilotIQ+Biofourmis Team!

What is the Senior Product Engineer role?

You’ll build features end to end for the people who run our care program: enrollment and sales teams, clinicians, and operations. You’ll work closely with Product to shape what we build, then own it through design, delivery and production. Our engineers also integrate with LLM models to lift the clinical and member experience. We treat those like any other feature: start from the user’s problem, ship something reliable, and measure whether it worked.

What we’re looking for

  • Extensive experience building production software, with real experience on both frontend and backend
  • A record of shipping user-facing features where you shaped the scope, not just implemented tickets
  • Clear communication with non-engineers, and comfort working directly with internal teams
  • Solid system design: data modeling, APIs, failure handling, observability, reliability, security by design
  • You test and monitor your own work, and you care when numbers are wrong
  • Regular use of AI coding assistants, and the judgment to know when not to trust them

Responsibilities

  • Work embedded with our stakeholders, Clinical, Sales and more: shadow their workflows, understand their goals, and identify the highest-impact problems to solve, including ones no one has written a requirement for yet.
  • Partner with Product to own product outcomes end to end: frame the problem, track success metrics, design the solution, ship it, measure the results, and iterate.
  • Build across the stack, including intuitive frontend experiences, reliable backend services, event-driven workflows, data flows, and third-party integrations.
  • Make sound system design decisions for our services and workflows, with clear thinking about data models, failure modes, scalability, and cost, and contribute to broader architectural decisions.
  • Build with AI coding agents as your primary way of working, and own the quality of what ships: clear specs and acceptance criteria up front, tests the agent’s code must pass, typed contracts, and careful review of every change that touches patient data, clinical logic, or billing.
  • Build AI-powered product features where they add real value, with structured outputs, evals, and safe fallback behavior.
  • Treat quality and safety as part of the job: protect patient data, maintain audit trails, ship behind feature flags with progressive rollouts, and verify data accuracy end to end.
  • Own the production services you build: monitor them, respond to incidents, find root causes, and continuously improve reliability, observability, and performance. Participate in on-call rotations and incident response.
  • Communicate decisions, tradeoffs, risks, and progress clearly to engineers, stakeholders, and leadership, in writing and in person.

Qualifications

  • 5+ years of professional software development experience, including significant time building and operating cloud-based production systems end to end.
  • Demonstrated system design skills: you’ve designed services, APIs, data models, and integrations that held up in production, and you can walk through the tradeoffs you made.
  • Sustained, hands-on use of AI coding agents on a production codebase, with concrete examples of how you kept quality high (testing strategy, review practices, and guardrails you put in place).
  • Experience shipping LLM-powered features, using frontier models, to production and operating them reliably, with evals and fallback behavior in place. Built the harness around the model: prompt and context management, versioned prompts, retries, timeouts and fallbacks when the model is slow, wrong or unavailable, and logging that doesn’t leak sensitive data.
  • Experience handling sensitive data securely, including access controls, encryption, and audit logging.
  • Experience in a startup or similarly fast-moving environment where engineers take broad ownership.
  • Bachelor’s degree in Computer Science, a related technical field, or equivalent practical experience.

Technical Experience

We expect candidates to be strong across the stack, with deeper expertise in at least one area. Our core stack includes:

  • React, with experience building polished, production-grade web applications.
  • Go, Java with Spring Boot, or a comparable backend language and framework.
  • AWS, including services such as Lambda, SQS, DynamoDB, and API Gateway.
  • MongoDB and Redis, or comparable data stores.
  • Docker and Kubernetes.
  • Infrastructure as code, such as Terraform, AWS CloudFormation, or AWS CDK.
  • Logging, monitoring, alerting, and observability tooling.
  • LLM provider APIs (such as Anthropic, OpenAI, or AWS Bedrock), including structured outputs, function calling and tool use, streaming, and graceful handling of rate limits, timeouts, and provider errors. Evaluating and monitoring AI features in production, including eval suites, tracing, and tracking output quality, latency, and cost.
  • AI coding agents such as Claude Code, Cursor, or Codex, along with the tooling that keeps their output safe: automated tests, typed interfaces, static analysis, and CI quality gates.

Bonus Points For

  • Experience in healthcare, digital health, telehealth, or care delivery.
  • Working knowledge of HIPAA as it applies to ingesting, processing, storing, and transmitting patient information.
  • Experience with model routing, cascading, or multi-provider orchestration for LLM workloads.
  • Experience in healthcare, digital health, telehealth, or care delivery.
  • Built polished, patient-facing mobile experiences (on React Native) that people use regularly, ideally for older adults or people with limited tech comfort: accessible design (large text, contrast, screen readers), simple onboarding, and engagement features like reminders and progress Experience building products for clinicians, care teams, sales teams, operational users, or older adults.
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