Software Engineer, AI/ML

Role overview

This role develops artificial intelligence and machine-learning capabilities for a healthcare data platform that helps organizations structure, manage, and exchange clinical information. As part of a product-focused laboratory team, you will shape AI strategy, design scalable solutions for customer needs, and contribute hands-on software in an Agile environment using short development cycles.

Responsibilities

- Act as the team’s AI/ML subject-matter expert, tracking relevant technologies, patterns, and opportunities. - Help document an AI strategy and align it with product priorities and organizational objectives. - Shape project scope, milestones, architecture, and solution designs from the outset. - Implement AI/ML features by writing production code, configuring external components, and prototyping emerging technologies. - Create maintainable code, automated unit and integration tests, and technical documentation. - Participate in design discussions, code reviews, pair programming, client meetings when needed, and broader technology planning. - Monitor priorities, deadlines, and backlogs while helping the team resolve technical issues and deliver committed work.

Requirements

- At least five years of experience in software architecture, full-stack development, or AI engineering. - Proven ability to design and document end-to-end architectures for complex software projects. - At least two years implementing advanced AI solutions such as semantic matching, retrieval-augmented generation, or document parsing for structured data. - Experience designing agentic systems with frameworks such as LangGraph, CrewAI, or the OpenAI Agents SDK. - Working knowledge of coding-assistance tools, Model Context Protocol, model ensembles, fine-tuning, and knowledge-graph databases such as Neo4j. - Familiarity with data-processing workflows involving technologies such as Databricks, Spark, or Iceberg. - Experience with human-in-the-loop AI workflows, model evaluation, results testing, and iterative refinement. - Strong coding practices, testing discipline, documentation skills, collaboration, and the ability to understand all code produced or assisted by AI tools.

Nice to have

- Experience mentoring teammates and contributing to technical architecture workshops. - Familiarity with shared internal libraries and developer-onboarding documentation.

Benefits and work setup

- Remote work environment with flexible time away, including paid time off, personal days, and sick days. - Health and medical coverage, retirement contribution options, life and disability coverage, and an employee assistance program. - Access to FHIR-focused learning and broader technical training resources. - A workplace that emphasizes inclusion, belonging, respectful collaboration, and accommodations for candidates who need them.