New 
Principal AI Engineer
 Spectraforce Technologies | |
 United States, Virginia, McLean | |
 Apr 24, 2026 | |
|
Job Title: Principal AI Engineer Location: McLean (open to Richmond) Duration: 7 months (chance of extension) Job Description: We are seeking a high-caliber Principal AI Engineer for a contract engagement to accelerate the implementation of Agentic AI solutions. This is a ""builder"" role requiring a rare blend of deep Generative AI expertise, full-stack Python mastery, and AWS cloud architecture. You will be responsible for moving AI from experimental prototypes to production-grade autonomous agents. Experience Requirements: Total Experience: 10+ years in Software Engineering. Python Mastery: 7+ years of professional backend development. AI/GenAI: 2+ years of hands-on implementation with LLMs (Claude, GPT, Llama). AWS: 5+ years architecting cloud-native applications. Key Responsibilities: Agentic Workflows: Design and deploy multi-agent systems using LLM orchestration frameworks (e.g., LangGraph, CrewAI) to automate complex cross-functional business processes, targeting measurable efficiency gains. Production RAG: Build and optimize high-performance Retrieval-Augmented Generation pipelines using Amazon Bedrock and vector databases (e.g., OpenSearch, Pinecone), with clear latency and accuracy targets. AI Integration: Develop robust FastAPI backends that make model outputs actionable for end-users. Collaborate with frontend engineers on React-based AI interfaces and streaming UI components. Responsible AI & Guardrails: Implement prompt safety mechanisms, output filtering, bias evaluation, and content moderation to ensure production LLM systems meet security and compliance standards. Engineering Excellence: Implement automated AI evaluation frameworks (e.g., Ragas, DeepEval), observability tooling (e.g., LangSmith, OpenTelemetry), and CI/CD pipelines for LLM prompts and code. Technical Stack AI: Claude, GPT-series, Hugging Face Transformers, PEFT, and LLM orchestration frameworks (e.g., LangChain, LangGraph). Agents: Experience with autonomous tool-use, function calling, and state management. Backend: Python 3.10+, Pydantic, FastAPI, and asynchronous programming. Cloud: Amazon Bedrock, SageMaker, Lambda (Serverless AI), and RDS/pgvector. Observability: Experience with AI-specific monitoring, tracing, and evaluation tooling. | |