AI Integration Engineer

Booz Allen Hamilton•Annapolis Junction, MD

2d•Remote

About The Position

As an AI Engineer, you will integrate AI-enabled capabilities into existing software systems by connecting models, inference endpoints, and orchestration components to production applications. You will implement AI features using established integration and software engineering patterns, ensuring these capabilities operate reliably, securely, and efficiently within distributed systems. You’ll contribute to evaluation and monitoring approaches, refine integration workflows, and collaborate with cross-functional teams to deliver scalable AI functionality. Your work will help bring AI from concept into real-world environments through thoughtful, well-structured engineering.

Requirements

3+ years of experience building and maintaining production software systems in Python
Experience integrating external services or APIs into distributed systems
Experience implementing inference request flows, including handling latency, token limits, and batching strategies
Experience writing integration tests for multi-service environments
Experience integrating large language models into production services, including managing inference requests, model responses, and error-handling flows
Knowledge of HTTP API design patterns, including authentication mechanisms such as OAuth2, API keys, or JWT
Knowledge of containerization and CI / CD pipelines
Ability to travel up to 25% of the time
TS/SCI clearance with a polygraph
Bachelor’s degree in CS, Engineering, or Data Science

Nice To Haves

Experience with message queues or event streaming, including Kafka, and SQS or SNS, and patterns for idempotency and handling out-of-order or duplicate events
Experience implementing resilience patterns such as retries with backoff, timeouts, and circuit breakers, to ensure reliable system behavior
Experience with cloud AI platform tooling such as AWS Bedrock AgentCore, Google Gemini Enterprise Agent Platform, or Microsoft Foundry Agent Service
Experience with Docker, Kubernetes, or Infrastructure-as-Code tooling
Experience with multi-step agentic workflows or orchestration concepts and how they integrate into existing systems
Experience with agent memory concepts such as session-level and persistent state, and how they relate to application logic
Experience with orchestration frameworks for AI-enabled systems such as LangGraph, CrewAI, or AutoGen, and supporting data stores such as Redis and Postgres

Responsibilities

Integrate AI-enabled capabilities into existing software systems by connecting models, inference endpoints, and orchestration components to production applications.
Implement AI features using established integration and software engineering patterns.
Ensure AI capabilities operate reliably, securely, and efficiently within distributed systems.
Contribute to evaluation and monitoring approaches for AI features.
Refine integration workflows for AI functionality.
Collaborate with cross-functional teams to deliver scalable AI functionality.