The OpportunityJoin the Proactive Communications & Notifications team as we build the systems that help Hinge Health determine what message a member receives, when they receive it, and which channel is most helpful. Our work brings together distributed backend services, data flows, and machine learning and AI capabilities to make member communication more relevant, timely, and actionable.
As an AI Engineer, you'll build and operate the backend systems that bring AI-powered product capabilities to members. You'll partner with senior engineers, ML Scientists, Data Engineering, Product, and other software engineers to design APIs, services, workflows, and data flows that are reliable in production.
This role is a strong fit for a backend-leaning software engineer who wants to apply distributed-systems skills to AI products. You'll help integrate, deploy, and operate models and AI services within product systems; model training and research are not the primary focus. MLOps experience is valuable, but the core expectation is strong software engineering, production execution, and operational ownership.
What You'll AccomplishIn your first 3 months- Learn the Proactive Communications & Notifications domain, service architecture, operational practices, and member-impact goals.
- Ship well-scoped improvements to APIs, services, asynchronous jobs, or workflows with guidance from senior engineers.
- Build familiarity with the team's testing, observability, deployment, and incident-response practices; participate in on-call or incident support as appropriate.
In your first 6 months- Own a medium-sized feature from planning through implementation, testing, rollout, and follow-up with minimal support.
- Integrate an ML- or AI-backed capability into a product workflow through clear interfaces, reliable data flows, and appropriate failure handling.
- Improve the correctness and operability of distributed systems by applying patterns such as retries, idempotency, versioning, graceful degradation, dashboards, and structured logging.
In your first year- Deliver multiple production initiatives that improve the relevance, timeliness, reliability, or maintainability of member communications.
- Trace and resolve issues across APIs, services, queues, databases, model-backed components, and data dependencies, raising risks and decisions early.
- Help strengthen the team through thoughtful code reviews, design documentation, pairing, onboarding support, and contributions to engineering practices.
Who You Are- You are a backend-minded software engineer who enjoys building reliable systems and learning how they behave in production.
- You can take a well-scoped problem from design through launch, break work into incremental changes, and ask for direction when complexity or ambiguity increases.
- You demonstrate effective communication through clear design notes, concise status updates, thoughtful code reviews, and early escalation of risks.
- You are a learn-it-all who welcomes feedback, builds depth in your primary technologies, and develops the judgment to make sound tradeoffs.
- You practice accountability by owning the quality, reliability, and follow-through of the systems you build.
- You lead at all levels: you are hands-on in the details, contribute to a positive team culture, and help teammates succeed through collaboration and knowledge sharing.
Basic Qualifications- 2+ years of non-internship, full-time professional software engineering experience.
- Experience building and operating backend services or distributed systems in production, including APIs, asynchronous processing, event-driven systems, workflows, or data-intensive services.
- Professional experience with at least one production programming language such as Python, TypeScript/JavaScript, Go, Java, Kotlin, or a comparable language, plus experience with software testing, observability, deployment, or production support.
Preferred Qualifications- Experience integrating ML- or AI-backed services into production products.
- Experience with AWS or another cloud platform and technologies such as Docker, Kafka, PostgreSQL, or equivalent systems.
- Experience with asynchronous processing, workflow orchestration, event-driven systems, or long-running state.
- Familiarity with CI/CD, service monitoring, model deployment, inference, or model versioning.
- Experience with Temporal, Step Functions, Kubernetes, Airflow, or comparable systems.
- Experience with generative AI, LLMs, retrieval, agents, or evaluation systems.
- Experience working in healthcare, digital health, fintech, or another regulated or data-sensitive domain.
Hinge Health Hybrid ModelThis is a hybrid role based in the San Francisco office, requiring in-person attendance three days per week for a full 8-hour business day. On remote days, employees are expected to work during core business hours with flexibility. The office is part of a dog-friendly workplace program.
