Software Engineer, Applied AI / Product

Role Summary

We help physicians to achieve independence by making it easier to start, operate, and grow their practices. We believe that the future of healthcare will not come from bureaucratic health care systems, but individual physicians. We are reducing the barriers for physicians to own their practice and make healthcare better for everyone.

We're a small team obsessed with deep thinking, speed, craftsmanship, and a customer-focused approach, committed to building the best care experience in healthcare with a 30-year horizon.

Our team has built and launched numerous products from 0-to-1, scaled startups from 10 to 300+ employees and from inception to over $1B in valuation, $60M+ ARR, and 100M+ MAU.

We are a group of technologists, physicians, engineers, and designers that are uniquely positioned to design and distribute the product in the healthcare industry.

We're building an agentic platform at the intersection of medicine and law, transforming complex, high-stakes casework into structured, actionable context. Our system handles patient records, legal workflows, and sensitive decisions, so reliability, clarity, and thoughtful engineering matter deeply.

As a software engineer, you'll work across the full stack: agent architectures, evals, the data and context that feed them, and the surfaces to interact with the platform and its harness.

In a given week, that might mean

• building and shipping a new workflow that takes over a step of the case process, driven by something a physician or our ops team flagged
• designing the eval framework that decides whether an agent's output is reliable enough to ship, while piping the feedback into our synthesized knowledge base
• improving how the platform ingests, indexes, and assembles the right case context for an agent to work from
• adding new tooling to the interfaces users interact with day to day, bringing more of the platform's context and agent capabilities into their workflow
• iterating quickly on a feature with direct input from users, refining the agents based on real-world usage and feedback
• setting the patterns and tooling for AI-native development that the rest of the team builds on

You'll be a great fit if you

• engineer for correctness and reliability, not just functionality
• are excited to work with frontier models, and care as much about the evals and guardrails around them as the models themselves.
• ship high-quality code fast, and can take a vague problem to a shipped solution without a spec.
• own problems end-to-end, from the agent logic to the interface a user actually uses.
• care about craft and the gap between something that works and something genuinely good to use.
• want to play long-term games with long-term people. We're building for a 30-year horizon, not a quick exit.

Traction / PMF

• We have strong product-market fit ($10MM+ ARR in under 14 months).
• We are profitable and funded by top-tier VCs in the healthcare vertical.
• We are looking for a generalist to work together to scale to hundreds of customers. You'll fit in if you want to take ownership of a product, codebase, or company from 1 to 100.

About the Company

ABOUT MOONLAKE

Moonlake is building the frontier of interactive world models: systems that generate, simulate, and reason over 3D environments for embodied AI, robotics and gaming. We develop the simulation infrastructure to build worlds (e.g., assets, scenes, digital twins) at scale.

Our team sits at the intersection of

Moonlake is building the next generation of AI infrastructure for interactive digital worlds. Our mission is to enable anyone to create, simulate, and interact with rich environments using natural language and multimodal inputs, turning simple ideas into worlds with structure, logic, and agents that can perceive and act.

Our team has raised $28M in seed funding from NVIDIA Ventures, Threshold Ventures, AIX ventures and notable angels including Naval Ravikant and Jeff Dean to build the foundational layer for the future of AI - powering everything from creative tools and games to robotics training, simulations, and digital twins. Our goal is to make building and experimenting with these environments as accessible and scalable as publishing video on the internet.

We are looking for exceptional research engineers and applied researchers to help push the frontier of interactive AI.

Embodied AI

Robotics simulation

Interactive 3D worlds

World models

Real-time generation

AI infrastructure