AI Engineer / Software Engineer - Federal Healthcare Program

AI Engineer – Federal Healthcare Programs

We are seeking multiple skilled AI Engineers to support a federal healthcare initiative focused on delivering secure, scalable, AI-driven digital health solutions. The Engineers will primarily work remotely with occasional meetings onsite in Washington DC so candidates must be local to the DMV area.

This role will be responsible for building, integrating, testing, and deploying enterprise-grade AI applications that leverage Generative AI, machine learning, cloud technologies, and modern software engineering practices to enhance healthcare delivery, operational performance, and improved patient outcomes.

This project requires software engineers with experience developing AI-enabled applications, integrating Large Language Models (LLMs), implementing Retrieval-Augmented Generation (RAG) solutions, and deploying AI capabilities within secure cloud environments.

Responsibilities

• Design, develop, deploy, and maintain production-ready AI applications and services.
• Build AI-powered APIs, microservices, and integrations supporting healthcare initiatives.
• Develop and implement RAG, agentic AI, and LLM-based solutions.
• Train, evaluate, optimize, and deploy machine learning and deep learning models.
• Create and manage MLOps pipelines for model development, deployment, monitoring, and lifecycle management.
• Develop AI-driven data pipelines for structured and unstructured healthcare data.
• Integrate AI solutions with enterprise systems, cloud platforms, and healthcare technologies using REST APIs and FHIR standards.
• Implement scalable, secure cloud-native architectures utilizing Docker, Kubernetes, and DevSecOps methodologies.
• Establish model evaluation frameworks to track performance, bias, drift, latency, hallucinations, and business impact.
• Partner with clinicians, architects, cybersecurity teams, product owners, and data scientists to deliver solutions.
• Produce technical documentation, architecture artifacts, implementation guides, and operational procedures.
• Participate in Agile development activities, including sprint planning, code reviews, demos, and continuous improvement efforts.
• Ensure compliance with Responsible AI principles, cybersecurity standards, privacy requirements, and federal regulations.

Required

• Ability to successfully complete a thorough federal background investigation.
• Bachelor’s degree in Computer Science, Software Engineering, Artificial Intelligence, Data Science, Informatics, or a related discipline.
• 8+ years of software engineering experience, including 3+ years delivering AI/ML or Generative AI solutions.
• Proven experience deploying AI solutions into production environments.
• Proficiency in Python and machine learning frameworks such as TensorFlow, PyTorch, or Scikit-Learn.
• Experience with LLM platforms including OpenAI, Anthropic, Llama, or similar technologies.
• Experience using frameworks such as LangChain, LlamaIndex, Semantic Kernel, LangGraph, or equivalent.
• Hands-on experience with prompt engineering, RAG, vector databases, AI agents, MLOps, Docker, Kubernetes, Git, CI/CD, and DevSecOps.
• Experience with Azure AI Foundry, Azure OpenAI, AWS Bedrock, Google Vertex AI, or comparable AI platforms.
• Strong communication, collaboration, and stakeholder management skills.

Desired Experience

• FHIR, HL7, SMART on FHIR, and electronic health record platforms such as Epic or Oracle Health/Cerner.
• Digital health solutions and/or population health analytics.
• Responsible AI, AI governance, explainable AI, and human-in-the-loop processes.
• Experience supporting federal healthcare organizations such as the VA, DHA, HHS, CMS, and/or NIH.

Desired Qualifications

• Master’s degree in AI, Computer Science, Data Science, Engineering, or a related field.
• Relevant AI or cloud certifications (Microsoft, AWS, Google, Databricks).
• Experience implementing enterprise AI platforms in secure cloud environments.
• Active Public Trust clearance.