Principal AI Engineer

Position Overview:

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.

Key Responsibilities:

Key Deliverables

• 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.

Qualifications:

• 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.