AI Engineer

Join a hands-on AI engineering team building and deploying LLM-powered applications. In this role, you'll implement core components of AI systems, including prompting, retrieval pipelines, and API integrations, while gaining experience with the tooling and infrastructure required to run AI workloads in production. You'll work across the full AI application lifecycle from data ingestion and retrieval to prompt engineering, evaluation, deployment, and production operations building secure, mission-focused AI solutions for federal clients.

Join us. The world can't wait.

You Have:

• 1+ years of experience in sof tware engineering, data engineering, or applied AI / ML
• Experience building applications in Python using frameworks such as FastAPI or Flask, and building and integrating applications using LLM APIs such as OpenAI, AWS Bedrock, or Azure OpenAI
• Experience implementing Retrieval-Augmented Generation ( RAG ) pipelines, including document ingestion, chunking, embeddings, retrieval workflows, and prompt augmentation
• Experience with vector databases such as FAISS, Pinecone, Weaviate, or OpenSearch Vector Search, and cloud environments, including AWS services such as S3, Lambda, EC2, IAM, and CloudWatch
• Experience using Git, basic CI / CD pipelines, and containerization with Docker
• Experience designing or consuming REST APIs and working with structured outputs such as JSON schemas and function or tool calling
• Knowledge of prompt engineering, prompt evaluation, and common LLM failure modes, including hallucinations, prompt injection, data leakage, jailbreak attempts, and grounding techniques
• Knowledge of prompt evaluation techniques and response quality testing
• Ability to obtain a TS/SCI clearance

Nice If You Have:

• Experience with orchestration frameworks such as LangChain or LlamaIndex
• Experience with embeddings via OpenAI, Cohere, or SentenceTransformers
• Experience with monitoring and logging tools such as CloudWatch or Datadog
• Experience deploying services using Docker Compose or Kubernetes
• Experience with structured logging and debugging distributed API failures
• Experience with AWS Secrets Manager or AWS Systems Manager Para met er Store
• Experience with asynchronous Python programming or background processing
• Experience with Model Context Protocol ( MCP ) or modern AI tool integration standards

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 $77,600.00 to $176,000.00 (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.

Job Number: R0246909
AI Engineer

The Opportunity:

Join a hands-on AI engineering team building and deploying LLM-powered applications. In this role, you'll implement core components of AI systems, including prompting, retrieval pipelines, and API integrations, while gaining experience with the tooling and infrastructure required to run AI workloads in production. You'll work across the full AI application lifecycle from data ingestion and retrieval to prompt engineering, evaluation, deployment, and production operations building secure, mission-focused AI solutions for federal clients.

Join us. The world can't wait.

You Have:

• 1+ years of experience in sof tware engineering, data engineering, or applied AI / ML
• Experience building applications in Python using frameworks such as FastAPI or Flask, and building and integrating applications using LLM APIs such as OpenAI, AWS Bedrock, or Azure OpenAI
• Experience implementing Retrieval-Augmented Generation ( RAG ) pipelines, including document ingestion, chunking, embeddings, retrieval workflows, and prompt augmentation
• Experience with vector databases such as FAISS, Pinecone, Weaviate, or OpenSearch Vector Search, and cloud environments, including AWS services such as S3, Lambda, EC2, IAM, and CloudWatch
• Experience using Git, basic CI / CD pipelines, and containerization with Docker
• Experience designing or consuming REST APIs and working with structured outputs such as JSON schemas and function or tool calling
• Knowledge of prompt engineering, prompt evaluation, and common LLM failure modes, including hallucinations, prompt injection, data leakage, jailbreak attempts, and grounding techniques
• Knowledge of prompt evaluation techniques and response quality testing
• Ability to obtain a TS/SCI clearance
• Bachelor's degree

Nice If You Have:

• Experience with orchestration frameworks such as LangChain or LlamaIndex
• Experience with embeddings via OpenAI, Cohere, or SentenceTransformers
• Experience with monitoring and logging tools such as CloudWatch or Datadog
• Experience deploying services using Docker Compose or Kubernetes
• Experience with structured logging and debugging distributed API failures
• Experience with AWS Secrets Manager or AWS Systems Manager Para met er Store
• Experience with asynchronous Python programming or background processing
• Experience with Model Context Protocol ( MCP ) or modern AI tool integration standards

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 $77,600.00 to $176,000.00 (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.

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