AI/ML Engineer

Leidos QTC Health Services•Reston, VA

About The Position

Do you crave a career that truly makes an impact in people’s lives? Do you thrive on problem-solving and finding solutions? Join a dedicated, tight-knit team that creates an immediate and meaningful impact every day Leidos QTC Health Services is seeking a midâtoâseniorâlevel AI Engineer who loves wrestling with large language models (LLMs) and building useful products. You will design and ship AIâpowered applications that leverage the latest LLMs while meeting the strict privacy and security requirements of the healthcare industry.

Requirements

Bachelor’s degree from an accredited college in Computer Science, Computer Engineering, Statistics, Data Science or another similar quantitative field. Additional experience in lieu of a degree may be considered.
9+ years in software engineering or machine learning, with 2+ years building production AI/ML systems.
Strong programming skills in Python and Typescript.
Experience with REST APIs and frameworks like Flask or FastAPI.
Familiarity with LangChain, LlamaIndex, HuggingFace Transformers, SGLang, and OpenAI API.
Experience with RAG architectures, including vector databases and GraphRAG approaches.
Experience deploying AI solutions using cloud platforms (AWS, Azure, or GCP).
Understanding of HIPAA compliance: handling PHI, encryption protocols, and vendor BAAs.
Experience in prompt engineering, prompt security, and evaluation strategies.
Familiarity with containerization, CI/CD, and MLOps pipelines

Nice To Haves

Experience in healthcare, life sciences, or other regulated industries.
Background in autonomous agents and orchestration frameworks (e.g., CrewAI, Strands, OpenAI Agents SDK).
Exposure to multi-modal models (e.g., GPTâ4o, Pixtral Large).
Knowledge of chain-of-thought reasoning and RLHF workflows.
Additional languages like Rust or Go; experience with microservices or event-driven architecture.

Responsibilities

Develop AIâpowered applications using stateâofâtheâart LLMs. You will build and deploy applications for our internal customers, selecting the right models (e.g., GPTâ4o, Claude Sonnet 4, Gemini 2.5 or openâsource alternatives).
Implement retrievalâaugmented generation (RAG) pipelines and agents using LangChain, LangGraph, LlamaIndex, and other emerging frameworks.
Integrate ML models with front-end apps, REST APIs, and backend systems.
Design and build end-to-end AI systems—ranging from chatbots and recommendation engines to vision-based pipelines.
Build robust logic around ML models to address edge cases, failovers, and complex business rules.
Leverage prebuilt models or services (e.g., OpenAI API, Azure Cognitive Services, HuggingFace) to accelerate development cycles.
Fineâtune and customize models using LoRA, prompt tuning, or RLHF techniques.
Occasionally perform custom model training—but more often fine-tune or adapt existing models to meet business needs.
Work with vector databases (e.g., Pinecone, Weaviate) and explore graph-based approaches (e.g., GraphRAG, Knowledge Graphs).
Ensure privacy and compliance with HIPAA, including encryption, PHI protection, and vendor due diligence.
Prototype multiâagent systems using frameworks like CrewAI or Stands SDK and evaluate emerging agent orchestration solutions.
Collaborate cross-functionally with product managers, data scientists, and compliance teams.
Mentor junior engineers, lead innovation discussions, and continuously evaluate emerging LLM architectures.