Software Engineer, Applied AI / Product

Embedding VC

$120K — $180K *
Healthcare
Less than 5 years of experience
Job Overview by Ladders

Qualifications

  • 5+ years of software engineering experience
  • Proficiency in full-stack development
  • Experience with AI and machine learning models
  • Strong problem-solving abilities
  • Ability to work independently and take ownership of projects
  • Passion for reliability and quality in engineering

Responsibilities

  • Build and ship new workflows for case processes
  • Design an evaluation framework for agent output reliability
  • Improve how the platform ingests and assembles case context
  • Add tooling to enhance user interfaces and workflows
  • Iterate on features using direct user feedback
  • Establish development patterns for AI-native systems

Benefits

  • Opportunity to work at the intersection of medicine and law
  • Collaborative environment focused on long-term goals
  • Exposure to cutting-edge models and technologies
  • Ownership of products and projects
  • Strong product-market fit and profitability
  • Support from top-tier VCs in a growing healthcare market
Full Job Description
The Role

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.

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