Artificial Intelligence/Machine Learning Engineer

The Opportunity:
As an experienced engineer, you know that agentic AI is transforming how organizations operate, make decisions, and deliver outcomes at speed. Your ability to design and build practical agentic systems that turn manual workflows into AI-enabled solutions makes you an integral part of delivering mission-focused outcomes. We need your technical depth, product mindset, and problem-solving drive to support the National Security Sector Rapid Prototyping team.

In this role, you will define, design, and deliver mission-relevant agentic AI prototypes in fast, iterative development cycles. You will collaborate with product leads, solution architects, and engineers to build, test, and deploy agent-based solutions that solve high-priority client challenges. You will apply best-fit frameworks and patterns, including agent orchestration, tool use, memory, and retrieval, while balancing solution quality, reliability, and cost.

You will be part of a small, high-performing team operating in a 4-week prototype lifecycle, where priorities shift quickly and multiple efforts may run in parallel. Success in this role requires adaptability, clear communication, strong execution, and ownership from concept through delivery.

Work with us to solve real-world challenges and shape the future of mission-focused agentic AI.

Join us. The world can't wait.

You Have:

• Experience building and delivering agentic AI applications in production or prototype environments
• Experience implementing agent orchestration frameworks
• Experience designing and implementing agent loops, tool-calling workflows, and multi-agent interaction patterns
• Knowledge of LLM platforms and providers, including AWS Bedrock and at least one additional provider, such as OpenAI or Ollama
• Knowledge of prompt engineering techniques for reliability, controllability, and task performance
• Knowledge of MCP usage and development, including integration of external tools and capabilities
• Ability to own technical delivery end to end in short-cycle environments, from design through deployment
• Ability to follow code review practices, document work, and maintain clean and reusable code
• HS diploma or GED

Nice If You Have:

• Experience implementing retrieval patterns for agentic systems, including RAG or GraphRAG is a plus
• Experience building agentic evaluation frameworks, test harnesses, or quality benchmarks
• Experience implementing observability for agentic systems, such as traces, telemetry, and failure analysis
• Knowledge of session and chat memory management strategies across multi-turn workflows
• Ability to design and document lightweight APIs that expose agent capabilities to downstream systems
• Bachelor's degree in Computer Science, Engineering, or a related technical field

Compensation

At Booz Allen, we celebrate your contributions, provide you with opportunities and choices, and support your total well-being. Our offerings include health, life, disability, financial, and retirement benefits, as well as paid leave, professional development, tuition assistance, work-life programs, and dependent care. Our recognition awards program acknowledges employees for exceptional performance and superior demonstration of our values. Full-time and part-time employees working at least 20 hours a week on a regular basis are eligible to participate in Booz Allen's benefit programs. Individuals that do not meet the threshold are only eligible for select offerings, not inclusive of health benefits. We encourage you to learn more about our total benefits by visiting the Resource page on our Careers site and reviewing Our Employee Benefits page.

Salary at Booz Allen is determined by various factors, including but not limited to location, the individual's particular combination of education, knowledge, skills, competencies, and experience, as well as contract-specific affordability and organizational requirements. The projected compensation range for this position is $99,000.00 to $225,000.00 (annualized USD). The estimate displayed represents the typical salary range for this position and is just one component of Booz Allen's total compensation package for employees. This posting will close within 90 days from the Posting Date.

Work Model
Our people-first culture prioritizes the benefits of collaboration, whether it occurs in person or virtually. To support engagement and effective communication, employees working virtually are generally expected to have their cameras on during meetings.

• Remote: If this position is listed as remote, there may still be occasions when you are required to work in person at a Booz Allen or customer facility.
• Hybrid: If this position is listed as hybrid, you will be expected to work from a Booz Allen facility frequently, in alignment with leadership expectations and the needs of the role. You may also be required to work from or visit a customer facility.
• Onsite: If this position is listed as onsite, work will primarily be performed at a Booz Allen office or customer facility, where employees will collaborate directly with colleagues and customers as required by the role.