Product Engineer; AI - Operations

Overview

Join the team shaping the future of healthcare. Medbridge is a dynamic software as a service company working with the country s largest healthcare providers to build technology solutions that help patients get better faster while decreasing the overall cost of care. Our Operations team is growing and looking for Product Engineer (AI) - Operations to join us.

Medbridge is establishing an AI Operations team to lead the integration of AI across our company and workflows. As a Product Engineer, you will own features end-to-end; you will partner directly with the Head of Operations to scope problems, design solutions, and execute rating at the intersection of AI, product development, and full-stack engineering, you will build and ship impactful tools in a high-ownership, high-judgment environment.

This role requires moving quickly, making decisions with incomplete information, and transforming ambiguous problems into finished products.

We are embedding AI into the core of our development process and product capabilities. Our engineers utilize AI throughout their workflows to reach real patients and clinicians. If you want to build alongside a team that treats AI as a first-class tool rather than a novelty, this is the place.

• Own stakeholder relationship across Medbridge s executive team, working with them to find the problems and AI-enabled solutions that can expedite, or remove, the current blockers in the business.
• Design, build, and ship AI-powered features across our internal teams, from the user interface to the backend services and AI workflows behind it.
• Build full-stack applications using AI-native engineering workflows and tools such as Claude, Cursor, Codex, and OpenAI and Anthropic APIs.
• Develop APIs, backend services, and automation pipelines that support intelligent product capabilities and production-ready deployments.
• Apply software engineering, Dev Ops, and MLOps best practices to the testing, deployment, monitoring, evaluation, and optimization of AI solutions.
• Partner closely with our Product and Engineering teams to turn ambiguous goals into scalable internal products.
• Use AI tooling throughout your workflow (coding, code review, testing, and planning) and help push the team s adoption forward.
• Research emerging AI technologies, LLM implementation patterns, and modern product engineering frameworks, and bring what works back to the team.
• Instrument what you ship and use usage data and evidence to decide what to build, fix, or kill next.

• 2+ years of professional experience in software engineering, product engineering, or full-stack application development.
• Hands-on experience delivering real AI-powered applications in production using tools such as Claude, Cursor, Codex, OpenAI, Anthropic, or similar AI development platforms.
• Practical experience integrating LLMs: prompt engineering, AI agents, generative AI workflows, or RAG architectures.
• Strong full-stack fundamentals with proficiency in a modern language such as Python, Type Script, or JavaScript, and a track record of building and deploying production-grade applications.
• Product instinct: you ask who the user is and what they actually need before writing code, and you push back on solutions that miss the point.
• A bias toward shipping and learning over endless planning, balanced with the judgment to know when something needs more care.
• Genuine enthusiasm for using AI to work better and faster, and the discernment to know where it helps and where it does not.
• Clear written and verbal communication. You can explain a tradeoff to an engineer and the same tradeoff to a non-engineer.
• Comfort with ambiguity and a track record of owning outcomes, not just tasks.

• Experience building evals or quality harnesses for LLM-based systems, and designing agent loops, tool integrations, or guardrails.
• Familiarity with vector databases, embeddings, semantic search, or orchestration and AI workflow automation frameworks.
• Familiarity with cloud platforms (AWS, Azure, or GCP) and containerization and deployment technologies such as Docker and Kubernetes.
• Strong product design instincts and the…