Senior Full-Stack Product Engineer, AI Products

Solv.

1d•$150,000 - $210,000•Remote

About The Position

Solv is building AI-powered healthcare infrastructure to simplify care for patients and healthcare teams. This role focuses on AI agents for scheduling and billing, but is a broader product-engineering position with evolving technologies. The ideal candidate is a senior generalist with strong web fundamentals, product judgment, curiosity, and ownership. You will collaborate with a product manager to define solutions and be responsible for technical decisions, execution, production quality, and outcomes. While prior AI-native team experience isn't required, hands-on AI work is essential, whether from production, prototypes, or personal projects. You will turn business and user problems into shipped improvements by building across the full stack, from frontend to backend services, APIs, data models, integrations, and AI workflows. This includes taking ideas from concept to production, building prototypes for rapid learning, developing reliable production systems, and improving AI systems through various data sources. You will design for uncertainty with robust testing, observability, and fallback mechanisms, and build enterprise healthcare products with a focus on privacy, reliability, and supportability. Exploring new AI capabilities while balancing speed, quality, safety, cost, and maintainability is key. You will extensively use AI development tools while maintaining ownership of technical decisions and production quality.

Requirements

5+ years of experience building and maintaining production web applications.
Strong senior-level fundamentals across frontend development, backend architecture, APIs, relational database design, testing, performance, and production debugging.
Take ownership of ambiguous problems: investigate deeply, create clarity, make sound decisions, and drive work forward without waiting for a fully specified solution.
Built or deeply explored an AI system beyond basic prompting or a thin API wrapper (e.g., RAG pipeline, automated or tool-using agent, evaluation system, AI workflow, model adaptation or post-training experiment).
Can explain what you built, why you chose the approach, where it failed, how you evaluated it, and what you learned.
Actively investigate emerging AI capabilities through hands-on experimentation and can identify where they may create meaningful product or business value.
Know how to move quickly without confusing a promising prototype with a production-ready system.
Work effectively with product managers while independently owning technical decisions and execution.
Willing to talk directly with customers, understand their workflows, and turn their problems into shipped improvements.
Motivated by measurable patient, customer, and business outcomes.
Bring high standards, low ego, and a willingness to dig into whatever problem will help the team succeed.

Nice To Haves

Experience with LLM applications, agents, retrieval, tool calling, evaluations, or AI observability.
Experience with voice systems, telephony, or conversational interfaces.
Experience with healthcare workflows, HIPAA, or protected health information.
Experience building enterprise products with complex integrations and operational workflows.
Experience with React, Remix, TypeScript, Python, FastAPI, Postgres, or similar technologies.

Responsibilities

Partner with product, design, customers, and engineers to turn business and user problems into shipped improvements.
Build across the full stack, including frontend experiences, backend services, APIs, relational data models, integrations, and AI-powered workflows.
Take ideas from early exploration through implementation, production rollout, and iteration.
Build scrappy prototypes to learn quickly, then develop reliable production systems when an opportunity is proven.
Improve AI systems using evaluations, production traces, customer feedback, product data, and operational signals.
Design for uncertainty through testing, observability, guardrails, fallbacks, auditability, and human escalation.
Build enterprise healthcare products that account for privacy, permissions, edge cases, data quality, reliability, and supportability.
Explore new AI capabilities while balancing speed, quality, safety, cost, customer value, and maintainability.
Use AI development tools extensively while retaining ownership of technical decisions and production quality.