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Agentic AI Machine Learning Engineer

Washington, DC

Pay
USD 99,000–225,000/year — pay source
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. Identity Statement
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Work setup
Unconfirmed
Employment
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What you’ll work on

Full posting
  • You’ll ensure that your team’s solutions consider the broader ecosystem and operating environment as well as future functionality and enhancements.

From the employer’s posting
As an experienced machine learning engineer, you understand good software is more than just a good user experience. To compete in today’s technical landscape, mission-oriented machine learning solutions must be architected, designed, and built to handle fast-moving data, to seamlessly scale with infrastructure based on system usage, and to expand based on evolving mission requirements. We’re looking for an engineer like you to create artificial intelligence (AI) and machine learning (ML) enabled solutions that help solve our toughest challenges facing the Defense and Intelligence sectors. On our team, you’ll design, create, and implement complete AI systems that will transform client operations, increase data accessibility, and optimize AI and ML systems. You’ll ensure that your team’s solutions consider the broader ecosystem and operating environment as well as future functionality and enhancements. Additionally, you’ll deepen your skill set in areas like software engineering, machine learning operations (MLOps), and software deployment and integration into a variety of different mission environments. Ready to transform the Defense and Intelligence sectors with software systems to aid data accessibility and AI and ML operationalization?

Tools in this posting

  • AWS
  • Docker
  • Grafana
  • Kafka
  • PyTorch
  • TensorFlow
  • Azure
  • Kubernetes
Source — Tool mentions in context
- 3+ years of experience working within data science or data research in a professional or academic environment, and training or deploying models across multiple modalities of data - 3+ years of experience working in cloud environments, including AWS and Azure - 2+ years of experience deploying and integrating production-grade ML models using tools, such as Docker and Kubernetes
- 3+ years of experience working in cloud environments, including AWS and Azure - 2+ years of experience deploying and integrating production-grade ML models using tools, such as Docker and Kubernetes - Experience with Large Language Models (LLM), Deep Learning (DL), and Reinforcement Learning (RL), and with tools and AI agent frameworks such as LangChain, LangGraph, PydanticAI, or llamaindex
- Experience in connecting Agents to APIs, Cloud platforms, or databases - Experience evaluating LLM performance and building observation layers for stakeholders, including Grafana, Langfuse, LangSmith, or Phoenix - Experience evaluating architectural tradeoffs and designing robust service-based software applications for scalable use
- Experience with project work in deep learning, computer vision, NLP, or signal processing - Experience deploying and managing data brokering solutions, including Kafka, Red Panda, Confluent, and other related services - Ability to adapt in a rapidly changing environment
Nice If You Have: - Experience with programming, including ML frameworks such as TensorFlow, PyTorch, llama.cpp, and vLLM - Experience with client engagements, client-facing project work, and business development

Job description

View original posting ↗

Agentic AI Machine Learning Engineer

The Opportunity: 

As an experienced machine learning engineer, you understand good software is more than just a good user experience. To compete in today’s technical landscape, mission-oriented machine learning solutions must be architected, designed, and built to handle fast-moving data, to seamlessly scale with infrastructure based on system usage, and to expand based on evolving mission requirements. We’re looking for an engineer like you to create artificial intelligence (AI) and machine learning (ML) enabled solutions that help solve our toughest challenges facing the Defense and Intelligence sectors.

On our team, you’ll design, create, and implement complete AI systems that will transform client operations, increase data accessibility, and optimize AI and ML systems. You’ll ensure that your team’s solutions consider the broader ecosystem and operating environment as well as future functionality and enhancements. Additionally, you’ll deepen your skill set in areas like software engineering, machine learning operations (MLOps), and software deployment and integration into a variety of different mission environments.

Ready to transform the Defense and Intelligence sectors with software systems to aid data accessibility and AI and ML operationalization?

Join us. The world can’t wait.

You Have:  

  • 3+ years of experience as a ML engineer and building production-grade ML solutions, including work involving LLMs, agents, or complex automation frameworks

  • 3+ years of experience working within data science or data research in a professional or academic environment, and training or deploying models across multiple modalities of data

  • 3+ years of experience working in cloud environments, including AWS and Azure

  • 2+ years of experience deploying and integrating production-grade ML models using tools, such as Docker and Kubernetes

  • Experience with Large Language Models (LLM), Deep Learning (DL), and Reinforcement Learning (RL), and with tools and AI agent frameworks such as LangChain, LangGraph, PydanticAI, or llamaindex

  • Experience in connecting Agents to APIs, Cloud platforms, or databases

  • Experience evaluating LLM performance and building observation layers for stakeholders, including Grafana, Langfuse, LangSmith, or Phoenix

  • Experience evaluating architectural tradeoffs and designing robust service-based software applications for scalable use

  • Ability to obtain a Secret clearance

  • Bachelor’s degree

Nice If You Have:  

  • Experience with programming, including ML frameworks such as TensorFlow, PyTorch, llama.cpp, and vLLM

  • Experience with client engagements, client-facing project work, and business development

  • Experience with project work in deep learning, computer vision, NLP, or signal processing

  • Experience deploying and managing data brokering solutions, including Kafka, Red Panda, Confluent, and other related services 

  • Ability to adapt in a rapidly changing environment

  • Possession of excellent verbal and written communication skills

  • Possession of excellent interpersonal, analytical, problem-solving, and organizational skills

  • Secret clearance

  • Master's degree

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.

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.

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. 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 or customer facility, in alignment with your leadership's expectations and the needs of the role.
  • Onsite: If this position is listed as onsite, work will primarily be performed full-time at a 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.

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  • Check the listed location, eligibility and core experience before starting.

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Source & posting history

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Location & working pattern

Washington, DC

Work Model Our people-first culture prioritizes the benefits of collaboration. 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 or customer facility, in alignment with your leadership's expectations and the needs of the role. - Onsite: If this position is listed as onsite, work will primarily be performed full-time at a customer facility, where employees will collaborate directly with colleagues and customers as required by the role.
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Status in our records
Active
First seen by us
Aug 13, 2026
Recorded sightings
70
Last seen by us
Oct 8, 2026

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