The Opportunity: 

As an AI/ML engineer, you know that the value of AI comes from applying it to real operational challenges. We need your software engineering skills and problem-solving mindset to help a defense client turn complex data and workflows into secure, reliable AI-enabled capabilities. As an agentic AI developer on our team, you’ll build, integrate, test, deploy, and maintain AI agents and supporting applications using Booz Allen’s Agent Foundry platform in an AWS environment.

In this role, you’ll contribute throughout the development lifecycle, connecting agents to enterprise data and tools, implementing retrieval and workflow orchestration, integrating ML capabilities, and evaluating application performance and reliability. You’ll collaborate with AI/ML engineers, data and cloud engineers, solutions architects, platform developers, and domain subject matter experts to translate mission needs into working software. Your contributions may support mission readiness assessments, capability gap analysis, knowledge discovery, workflow automation, and computer vision or geospatial analysis for infrastructure and asset management.

You’ll take responsibility for assigned features, contribute to technical design discussions and code reviews, and work with teammates to troubleshoot issues and improve solutions. Building on capabilities provided by the platform team, you’ll help deliver mission-focused agents with appropriate security controls, traceable outputs, and human oversight. You’ll have opportunities to apply your technical strengths while expanding your experience across agentic AI, ML, and cloud software engineering.

Work with us to turn advances in AI into dependable capabilities that help defense organizations make informed decisions and accomplish their missions.

Join us. The world can’t wait.

You Have:  

• 2+ years of experience developing production-grade Python software, including back-end applications, APIs, or data services
• 2+ years of experience developing, integrating, or deploying AI/ML-enabled applications, including hands-on implementation of applications using large language models (LLMs), retrieval-augmented generation, or agentic workflows
• Experience contributing to a software development project using Git-based version control, code reviews, automated testing, and CI/CD
• Experience evaluating an AI/ML application using test datasets, performance metrics, error analysis, or documented user feedback to identify and implement improvements
• Knowledge of LLM and agent development patterns, including tool or function calling, context management, retrieval, workflow orchestration, and human-in-the-loop controls
• Knowledge of AWS fundamentals, including identity and access management (IAM), compute, storage, networking, and managed AI/ML services, and secure development practices such as least-privilege access, secrets management, and input and output validation
• Ability to translate a mission use case into an implemented and tested software feature and communicate its design, results, and limitations to engineering teammates and domain subject matter experts
• Ability to obtain a Secret clearance
• Bachelor’s degree in CS, Software Engineering, Data Science, or Engineering and 5+ years of experience in software engineering, AI/ML engineering, data engineering, or cloud engineering, or Master’s degree in CS, Software Engineering, Data Science, or Engineering and 2+ years of experience in software engineering, AI/ML engineering, data engineering, or cloud engineering

Nice If You Have:  

• Experience developing or deploying AI-enabled applications on AWS using services such as Amazon Bedrock, Amazon SageMaker AI, AWS Lambda, Amazon S3, Amazon DynamoDB, Amazon OpenSearch Service, Amazon ECS, or Amazon EKS
• Experience implementing agent orchestration, tool integration, or knowledge retrieval using Strands Agents, LangGraph, LangChain, Model Context Protocol, Temporal, vector databases, or knowledge graphs
• Experience building and operating production data pipelines, including ETL/ELT, batch or streaming ingestion, data quality validation, schema management, metadata, and lineage, using technologies such as SQL, Python, AWS Glue, Apache Spark, Databricks, or Apache Airflow
• Experience implementing AWS DevOps or MLOps practices, including automated deployments, containerization, Infrastructure-as-Code, observability, and troubleshooting, using technologies such as Docker, Kubernetes, Terraform, AWS CDK, GitHub Actions, Amazon CloudWatch, or OpenTelemetry
• Experience securing AWS-hosted models, inference endpoints, or agentic applications through least-privilege IAM, service authentication and authorization, secrets management, encryption, network isolation, and audit logging, including safeguards against prompt injection, sensitive-data exposure, and unauthorized tool execution
• Experience developing computer vision, multimodal, or geospatial solutions for image classification, object detection, segmentation, change detection, or asset inspection, using technologies such as PyTorch, TensorFlow, OpenCV, GDAL, Rasterio, GeoPandas, or Open3D, and processing georeferenced imagery, LiDAR, photogrammetry, or point clouds
• Knowledge of software and AI/ML delivery requirements in AWS GovCloud or other regulated, restricted, or classified environments, including RMF, STIG-aligned development, vulnerability remediation, or authorization-to-operate evidence
• Secret clearance
• AWS Professional-level, AWS Certified Security – Specialty, AWS Certified SysOps Administrator – Associate, or AWS Associate-level Certification such as AWS Certified Solutions Architect – Associate, AWS Certified Developer – Associate, AWS Certified CloudOps Engineer – Associate, AWS Certified Data Engineer – Associate, or AWS Certified Machine Learning Engineer – Associate Certification
• CompTIA Security+ Certification

Clearance: 

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

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.

Identity Statement

As part of the hiring process, we will ask you to complete an identity verification process that leverages advanced biometrics and artificial intelligence to ensure authenticity and protect against identity fraud. You are expected to be on camera during interviews and assessments. We reserve the right to take your picture to verify your identity and prevent fraud.

Candidate AI Usage Policy

AI is a part of our daily work at Booz Allen, and we are committed to the responsible and ethical use of AI tools. However, we want to ensure a fair candidate process based on your own skills and knowledge. As part of this commitment, the use of artificial intelligence (AI) or other tools to assist with responses during interviews (whether in-person or virtual) is prohibited unless permission is explicitly provided.

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.

Commitment to Non-Discrimination

All qualified applicants will receive consideration for employment without regard to disability, status as a protected veteran or any other status protected by applicable federal, state, local, or international law.