Agentic AI Engineer

Booz Allen Hamilton•Arlington, VA

1d•$99,000 - $225,000

About The Position

As an experienced engineer, you know how to design, develop, and deliver production-grade agentic AI systems that demonstrate the practical value of generative AI, large language models (LLMs), and autonomous workflows. This role combines deep technical expertise with strong product skills to design AI applications that leverage prompting, retrieval-augmented generation (RAG), agentic orchestration, evaluation pipelines, and human-in-the-loop systems to deliver measurable impact. You will architect modular, reusable AI application patterns, integrate multiple model providers such as cloud-hosted, local, and hybrid, and apply modern GenAI stack capabilities, including structured prompting, tool use, workflow orchestration, and multi-modal reasoning. You will design solutions deployable across various contexts, from cloud-hosted platforms to portable, self-contained builds, optimizing for latency, cost efficiency, observability, and safety. You will rapidly prototype and iterate using AI-assisted development tools, validating hypotheses through evaluation-driven development and continuous experimentation. In this role, you’ll define the direction of mission-critical agentic systems by selecting and combining prompting strategies, RAG architectures, agentic workflows, and fine-tuned or foundation models as appropriate. You’ll be part of a large community of AI and ML engineers across the company, collaborating with data engineers, data scientists, solutions architects, and product owners to deliver world-class solutions. Join us. The world can’t wait.

Requirements

2+ years of experience designing, developing, or deploying AI-driven systems, including autonomous agents, LLM-based systems, or automated decision pipelines
2+ years of experience with an object-oriented programming language such as Python, and applying it to AI/ML solution development
Experience with agent orchestration frameworks such as LangChain, AutoGen, CrewAI, or custom agent frameworks
Experience integrating LLMs, GPT-class models, or multimodal models into applications, pipelines, or mission systems
Experience with RAG architectures, evaluation methodologies, experimentation workflows, and asynchronous or event-driven programming patterns
Experience working in cross-functional delivery environments with data scientists, ML engineers, SREs, product managers, and security teams, and creating reference architectures and technical roadmaps
Secret clearance
Bachelor's degree

Nice To Haves

Experience with agent frameworks, interoperability standards, and multi-agent patterns such as MCP, A2A, LangGraph, or equivalent
Experience with model fine-tuning, prompt tuning, domain adaptation, or reinforcement learning from human or AI feedback
Experience designing evaluation suites or safety testing frameworks for AI systems, and integrating AI systems with external tools, APIs, or enterprise systems via tool-calling or computer-use patterns

Responsibilities

Design, develop, and deliver production-grade agentic AI systems.
Leverage prompting, retrieval-augmented generation (RAG), agentic orchestration, evaluation pipelines, and human-in-the-loop systems.
Architect modular, reusable AI application patterns.
Integrate multiple model providers (cloud-hosted, local, and hybrid).
Apply modern GenAI stack capabilities, including structured prompting, tool use, workflow orchestration, and multi-modal reasoning.
Design solutions deployable across various contexts, optimizing for latency, cost efficiency, observability, and safety.
Rapidly prototype and iterate using AI-assisted development tools.
Validate hypotheses through evaluation-driven development and continuous experimentation.
Define the direction of mission-critical agentic systems by selecting and combining prompting strategies, RAG architectures, agentic workflows, and fine-tuned or foundation models.
Collaborate with data engineers, data scientists, solutions architects, and product owners.