AI Engineer

Booz Allen Hamilton•Washington, DC

6d•$99,000 - $225,000•Hybrid

About The Position

We're looking for an AI Engineer to design, build, and operate production-grade AI systems at scale to own the full lifecycle of agentic applications and ML solutions, from data pipelines and model development to evaluation, observability, and performance optimization. You'll own production AI/ML solutions end to end by building and deploying applications like multi-agent systems in cloud environments. You'll ensure systems are observable and performant, implementing tracing, metrics, and optimizing latency, caching, and retrieval, while designing and evaluating RAG pipelines, applying traditional ML where appropriate, and using AI-assisted coding tools to accelerate delivery.

Requirements

3+ years of experience building production systems and applications, including AI/ML applications
2+ years of experience developing Generative AI applications using LLMs, RAG frameworks, and vector stores
Experience designing and building APIs and services with FastAPI, Flask, or Node.js
Experience working in cloud-native environments like AWS and Azure and developing scalable solutions with cloud services like Bedrock/AI Foundry, SageMaker/AI Studio, EKS/ECS, S3, IAM, CloudWatch
Experience with agent orchestration frameworks, such as LangGraph and Strands, and tool or function calling patterns
Experience implementing observability such as OpenTelemetry, Datadog, or CloudWatch and performance metrics pipelines with dashboards
Experience using AI-assisted coding tools such as Copilot, Codex, and Claude Code for complex development tasks
Experience deploying models, agents, or applications via CI/CD
Ability to obtain a Secret clearance
Bachelor's degree in CS, Engineering, or STEM field

Nice To Haves

Experience supporting DoW clients or other federal mission environments
Experience with advanced agentic patterns including prompt caching, guardrails, agentic memory, Model Context Protocol (MCP), and agentic deployment strategies
Experience with end-to-end chatbot or agent to agent (A2A) development
Experience with enterprise data and ML platforms such as Databricks or Snowflake
Experience in creating and managing large data processing pipelines
Master’s degree

Responsibilities

Design, build, and operate production-grade AI systems at scale.
Own the full lifecycle of agentic applications and ML solutions, from data pipelines and model development to evaluation, observability, and performance optimization.
Build and deploy applications like multi-agent systems in cloud environments.
Ensure systems are observable and performant, implementing tracing, metrics, and optimizing latency, caching, and retrieval.
Design and evaluate RAG pipelines.
Apply traditional ML where appropriate.
Use AI-assisted coding tools to accelerate delivery.