Principal Software Engineer

Principal AI/ML Engineer | Healthcare AI

I’ve partnered with a growing healthcare AI company that builds intelligent software for healthcare organizations. Their products use machine learning, generative AI and AI agents to cut through complex clinical and administrative work, so teams can make faster, better-informed decisions about patient care. Explainability, security and human oversight are built into how they work, and as they grow, they’re investing heavily in their AI engineering team.

They’re now looking for a Principal AI/ML Engineer to shape and lead their AI engineering work. This is a senior, hands-on role. You’ll set the technical direction for AI, ML, generative AI and agentic automation, then guide those solutions from architecture through to production. Much of the work supports a US government healthcare agency, so you’ll be building secure, reliable AI that improves services at real scale. You’ll work closely with engineering, product and agency stakeholders, and you’ll have real influence over the platform, the standards and the team that grows around it.

What you’ll be doing

• Architecture and strategy. Define the AI/ML and generative AI architecture and engineering strategy. Design scalable systems for machine learning, deep learning, LLMs, RAG, multimodal AI and AI agents. Set standards for development, inference, evaluation, observability and governance. Assess emerging AI platforms and make build-versus-buy calls. Create reusable frameworks the wider team can build on.
• Agentic AI and automation. Architect single-agent and multi-agent solutions that automate real operational work. Put clear guardrails, authorization and human-in-the-loop controls around them.
• Generative AI and ML engineering. Lead the delivery of production-grade LLM and ML applications, including RAG solutions. Own model selection, prompt engineering and optimization strategy. Tackle the hard problems: hallucination, bias, data leakage and prompt injection.
• Production delivery and MLOps. Establish MLOps and LLMOps practices, design cloud deployment architectures, and put monitoring, observability, versioning and rollback in place.
• Technical leadership. Mentor engineers, run design, architecture and code reviews, and define the AI roadmap and proofs of concept.

What you’ll need

• 8+ years of software engineering or AI/ML experience.
• Strong hands-on Python, plus deep experience across machine learning, LLMs, cloud platforms, MLOps and security.
• Experience with MS SQL Server, including writing queries, designing schemas and tuning performance.
• A bachelor’s or master’s degree in a related field, such as data science, machine learning or computer science.
• US citizenship.

Nice to have

• An active security clearance.
• Experience working with government agencies or in healthcare.
• Claude Certified Architect. If you don’t hold it yet, you’ll need to earn it within six months of joining.
• Tools: Python, PyTorch, TensorFlow and scikit-learn; LangGraph and LangChain; OpenAI, Azure OpenAI, Anthropic and Gemini models.
• Vector databases: Pinecone, OpenSearch, Elasticsearch, pgvector or Milvus.
• Cloud and MLOps: AWS (including Bedrock), Azure or GCP; Docker, Kubernetes, MLflow and Kubeflow.
• JavaScript or Node.js, which may become the main runtime for AI services.
• A patent in a related field.

What’s on offer

• Competitive salary
• Healthcare
• 401(k)
• Bonus
• Remote, with occasional in-person attendance

If this sounds like a good fit for you, or someone you know, please apply, and reach out to