Job description

AI/ML Engineer, Lead The Opportunity: As an AI/Machine Learning Engineer, you'll lead the design, development, and deployment of advanced AI and ML systems that support enterprise products and strategic initiatives. This role combines deep technical expertise with the ability to collaborate across engineering, product, and data teams. The ideal candidate has extensive experience building production-grade ML models, optimizing model performance, and guiding architectural decisions around scalable AI systems. As an experienced engineer, you know that machine learning is critical to understanding and processing massive datasets. Your ability to conduct statistical analyses on business processes using ML techniques makes you an integral part of delivering a customer-focused solution. What You'll Do: • Design, develop, and deploy machine learning models and AI systems for large-scale production environments. • Lead end-to-end ML lifecycle processes including data exploration, feature engineering, experimentation, model training, evaluation, and deployment. • Architect scalable ML pipelines and infrastructure using modern frameworks and cloud technologies. • Collaborate with cross-functional stakeholders to translate business requirements into ML-driven solutions. • Mentor junior engineers and contribute to best practices, coding standards, and technical excellence. • Evaluate and integrate emerging AI technologies, tools, and frameworks aligned with organizational goals. • Monitor and optimize deployed models for accuracy, performance, drift, reliability, and ethical considerations. • Partner with data engineering teams to ensure high-quality datasets and robust pipeline integrations. • Design, build, and deploy large language model (LLM) and agentic AI solutions, including multi-agent orchestration, tool use, autonomous workflows, and retrieval-augmented generation (RAG). • Optimize and deploy AI/ML models for edge environments, applying techniques such as quantization, pruning, and distillation to enable low-latency inference on resource-constrained and edge devices. Work with us to solve real-world challenges and define ML strategy for law enforcement and homeland security clients. Join us. The world can’t wait. You Have:  • 8+ years of experience developing and deploying machine learning models in production environments • Experience in Python and ML frameworks • Experience with cloud platforms, such as AWS, Azure, or GCP, and tools for scalable ML systems, such as SageMaker, Azure ML, or Vertex AI • Experience building data pipelines • Experience with MLOps practices including CI/CD for ML, model versioning, monitoring, and deployment automation • Knowledge of ML algorithms, statistics, model optimization, and evaluation methodologies • Ability to design distributed systems and work with microservice-based architectures • Ability to communicate complex technical concepts clearly to non-technical stakeholders • Ability to obtain and maintain a Public Trust or Suitability/Fitness determination based on client requirements • Bachelor’s degree in a Computer Science, Data Science, or Engineering field Nice If You Have:  • Experience with LLMs, generative AI, RAG systems, and prompt engineering • Experience building agentic AI systems, including multi-agent frameworks, autonomous agents, tool and function calling, orchestration libraries such as LangChain, LangGraph, LlamaIndex, AutoGen, or CrewAI • Experience with edge AI optimization and deployment, including model quantization, pruning, and distillation, and deployment to edge and embedded hardware using frameworks such as TensorRT, ONNX Runtime, OpenVINO, or TensorFlow Lite • Experience with open-source containerization and container orchestration technologies, including Docker and Kubernetes • Experience with MLOps for production and machine learning workloads • Possession of strong problem-solving skills • Master’s degree preferred; Doctorate degree a plus Vetting: Applicants selected will be subject to a government investigation and may need to meet eligibility requirements of the U.S. government client. 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 $128,700.00 to $292,000.00 (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. 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.

Requirements

Must-haves

Design, develop, and deploy machine learning models and AI systems for large-scale production environments.
Lead end-to-end ML lifecycle processes including data exploration, feature engineering, experimentation, model training, evaluation, and deployment.
Architect scalable ML pipelines and infrastructure using modern frameworks and cloud technologies.
Collaborate with cross-functional stakeholders to translate business requirements into ML-driven solutions.
Mentor junior engineers and contribute to best practices, coding standards, and technical excellence.
Evaluate and integrate emerging AI technologies, tools, and frameworks aligned with organizational goals.
Monitor and optimize deployed models for accuracy, performance, drift, reliability, and ethical considerations.
Partner with data engineering teams to ensure high-quality datasets and robust pipeline integrations.
Design, build, and deploy large language model (LLM) and agentic AI solutions, including multi-agent orchestration, tool use, autonomous workflows, and retrieval-augmented generation (RAG).
Optimize and deploy AI/ML models for edge environments, applying techniques such as quantization, pruning, and distillation to enable low-latency inference on resource-constrained and edge devices.
Work with us to solve real-world challenges and define ML strategy for law enforcement and homeland security clients.
Join us. The world can’t wait.
8+ years of experience developing and deploying machine learning models in production environments
Experience in Python and ML frameworks
Experience with cloud platforms, such as AWS, Azure, or GCP, and tools for scalable ML systems, such as SageMaker, Azure ML, or Vertex AI
Experience building data pipelines
Experience with MLOps practices including CI/CD for ML, model versioning, monitoring, and deployment automation
Knowledge of ML algorithms, statistics, model optimization, and evaluation methodologies
Ability to design distributed systems and work with microservice-based architectures
Ability to communicate complex technical concepts clearly to non-technical stakeholders
Ability to obtain and maintain a Public Trust or Suitability/Fitness determination based on client requirements
Bachelor’s degree in a Computer Science, Data Science, or Engineering field
Experience with LLMs, generative AI, RAG systems, and prompt engineering

Nice-to-haves

Master’s degree preferred; Doctorate degree a plus

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

aimlmachine learningllmpythonawsazuregcpci/cddockerkubernetes

Platform: booz-allen
Effort: medium

Benefits

Benefits detected in the listing.

Professional Development