Agentic AI Field Engineer - Deploying Smart Agents

Booz Allen Hamilton

McLean (VA)

On-site

USD 99,000 - 225,000

Full time

5 days ago

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Benefits offered by this job

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Job summary

Booz Allen Hamilton is seeking an experienced AI-forward engineer to join the Global Defense Disruption Cell in McLean, VA. You will map how programs actually operate, design deterministic and agentic AI solutions, and embed with teams to convert workflows into automated agents that are observable and auditable from day one.

You'll work to deploy AI agents across enterprise tools and data sources, develop evaluation frameworks, and drive adoption while training workforces to supervise

Qualifications

5+ years of experience in software engineering, machine learning engineering, technical advisory, or solutions engineering roles.
2+ years of experience building applications with generative and agentic AI technologies, including LLMs, RAG, MCP, or multi-agent orchestration.
Experience deploying an LLM-powered system or AI agent into a production environment, including evaluation, monitoring, and iteration after launch.
Experience developing production code in Python or TypeScript.
Experience integrating with enterprise systems and data sources, such as ERP, CRM, ITSM, or SharePoint platforms.
Experience working directly with customers or business stakeholders to elicit requirements, map business processes, and guide adoption of new technology.
Knowledge of evaluation techniques for non-deterministic systems, including golden datasets, regression testing, and human-in-the-loop feedback.
Ability to operate independently in ambiguous, fast-moving environments and communicate with audiences ranging from engineers to executives.
Ability to obtain a Secret clearance.

Responsibilities

Embed with program teams to observe and document how work actually happens, including workflows, systems, data flows, decision points, and the exception paths that never make it into the documented process.
Produce operating maps and automation roadmaps that prioritize high-volume workflows by expected value and risk, and decide where deterministic software, agent judgment, and human-in-the-loop approval each belong.
Design, build, and deploy AI agents that reason, plan, and act across the program's existing tools, APIs, and data sources.
Build on the systems teams already use rather than forcing a migration.
Develop evaluation frameworks, golden datasets, and regression tests that turn non-deterministic behavior into evidence, and scale agents from shadow mode to increasing autonomy to production.
Instrument everything including audit trails, monitoring, and metrics that let program leadership see exactly what agents are doing and what value they deliver in hours saved, risk reduced, and outcomes improved.
Drive adoption and change management, train the workforce, redesign roles around supervision of automation, and de-risk the transformation for the people living through it.
Codify what you learn into playbooks, reusable components, and field feedback for the Disruption Cell, and elevate blockers through direct reach-back so no engagement stalls on access or politics.

Skills

Software engineering

Machine learning engineering

Technical advisory

Solutions engineering

Generative AI

Agentic AI

LLMs

Python

TypeScript

Enterprise systems

Education

Bachelor's degree

Master's degree

Tools

Python

TypeScript

ERP

CRM

ITSM

SharePoint

Job description

You'll work to deploy AI agents across enterprise tools and data sources, develop evaluation frameworks, and drive adoption while training workforces to supervise

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