Agentic AI Engineer

Responsibilities

• Embed agentic AI capabilities into existing enterprise systems and workflows, covering API integration, process automation, and end-user adoption.
• Architect intelligent agents that can reason, plan, and act within complex environments.
• Develop and deploy collaborative multi-agent systems using Model Context Protocol (MCP) and Agent-to-Agent (A2A) protocols.
• Build advanced retrieval augmented generation pipelines that fuse unstructured data with Knowledge Graphs to improve reasoning and context retention.
• Fine-tune Small Language Models for domain-specific tasks and optimize performance on edge devices.

Requirements

• 6+ years of software development experience.
• 3+ years in cloud environments (AWS and Azure), evaluating architectural tradeoffs, delivering scalable service-based software, and using LangChain, LangGraph, AutoGen, PydanticAI, CrewAI, or LlamaIndex.
• Experience with Model Context Protocol (MCP) for tool integration, A2A for collaboration, RAG architectures and Knowledge Graphs, memory architectures for long-running agents (episodic, semantic, and working memory), and agent benchmarking frameworks such as GAIA, SWE-bench, or custom eval harnesses.
• Experience with tool or function calling patterns across multiple LLM providers.
• Experience fine-tuning LLMs or Small Language Models.
• Knowledge of modern software design patterns, including microservice design or edge computing.
• Ability to translate agentic AI capabilities into practical enterprise workflows bridging technical implementation and business processes.
• Adaptability in a rapidly changing environment and the ability to navigate ambiguity.
• Ability to obtain a Secret security clearance.
• Bachelor’s degree in Computer Science or Computer Engineering.

Technologies

• AWS, Azure
• LangChain, LangGraph, AutoGen, PydanticAI, CrewAI, LlamaIndex
• Model Context Protocol (MCP), Agent-to-Agent (A2A)
• Knowledge Graphs, Small Language Models (SLMs)
• TensorFlow, PyTorch, llama.cpp, vLLM
• Cursor, Windsurf
• GAIA, SWE-bench

Benefits

• Health benefits
• Life benefits
• Disability benefits
• Financial benefits
• Retirement benefits
• Paid leave
• Professional development
• Tuition assistance
• Work-life programs
• Dependent care

Work model

• Remote: May require in-person work at Booz Allen or customer facilities on occasion.
• Hybrid: Frequent in-office work at Booz Allen facilities, with possible customer visits as needed by the role.
• Onsite: Primary work performed at Booz Allen offices or customer facilities, with direct collaboration as required.

Clearance

• Applicants selected will be subject to a security investigation and may need to meet eligibility requirements for access to classified information.

Compensation

• Salary range USD 112,800 to 257,000 per year, determined by location, education, experience, skills, and contract-specific considerations.

Identity verification

As part of the hiring process, candidates may undergo identity verification that uses biometrics and artificial intelligence. Interviews and assessments may require being on camera, and Booz Allen may capture images to verify identity and prevent fraud.

Candidate AI usage policy

AI tools are part of Booz Allen's daily work, with an emphasis on responsible use. Use of AI to assist with interview responses is prohibited unless explicit permission is provided.

Non-discrimination

All qualified applicants will receive consideration for employment without regard to disability, protected veteran status, or any other status protected by applicable law.