Principal AI Engineer {McLean or #2 Richmond}

Job Title: Principal AI Engineer (Contract)
Location: McLean, VA or Richmond, VA (Hybrid)
Engagement Type: 7-Month Contract (with possible extension)

Overview
We are seeking a high-caliber Principal AI Engineer to accelerate the implementation of cutting-edge Agentic AI solutions. This is a hands-on builder role requiring a rare combination of deep Generative AI expertise, full-stack Python mastery, and strong AWS cloud architecture experience. You will play a critical role in transforming AI from experimental prototypes into production-grade autonomous systems that deliver real business value.

Key Responsibilities

• Agentic Workflows:
  Design, build, and deploy multi-agent systems using LLM orchestration frameworks (e.g., LangGraph, CrewAI) to automate complex cross-functional business processes, with a focus on measurable efficiency gains.
• Production RAG Systems:
  Develop and optimize high-performance Retrieval-Augmented Generation (RAG) pipelines using Amazon Bedrock and vector databases (e.g., OpenSearch, Pinecone), meeting defined latency and accuracy targets.
• AI Integration:
  Build scalable FastAPI backends that operationalize AI model outputs. Collaborate with frontend teams to support React-based AI interfaces, including real-time and streaming user experiences.
• Responsible AI & Guardrails:
  Implement safety mechanisms such as prompt controls, output filtering, bias evaluation, and content moderation to ensure compliance, security, and ethical AI use.
• Engineering Excellence:
  Establish robust AI evaluation frameworks (e.g., Ragas, DeepEval), observability systems (e.g., LangSmith, OpenTelemetry), and CI/CD pipelines for both code and prompt lifecycle management.

Required Experience

• Software Engineering: 10 years of professional experience
• Python Development: 7 years of backend development using Python
• AI / Generative AI: 2 years of hands-on experience implementing LLM-based solutions (e.g., Claude, GPT, Llama)
• AWS Cloud Architecture: 5 years designing and deploying cloud-native applications

Technical Skills

• AI & ML:
  Claude, GPT-series models, Hugging Face Transformers, PEFT, LangChain, LangGraph
• Agent Systems:
  Experience with autonomous agents, tool usage, function calling, and state management
• Backend Development:
  Python 3.10 , FastAPI, Pydantic, asynchronous programming
• Cloud & Infrastructure:
  Amazon Bedrock, SageMaker, AWS Lambda (serverless AI), RDS, pgvector
• Observability & Evaluation:
  Experience with AI monitoring, tracing, and evaluation frameworks

What Success Looks Like

• Production-ready AI agents deployed with measurable business impact
• Reliable, scalable RAG systems with strong performance benchmarks
• Secure, compliant AI systems aligned with Responsible AI standards
• Mature engineering practices applied to AI development lifecycle