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64 of 472 matching · page 1 of 2

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TypeAgent infrastructure126 Agent engineering153 Developer tooling2 Applied research11 Forward deployed179 Other1

ModeRemote92 Hybrid95 On-site72 Location TBD213

LevelJunior18 Mid-level101 Senior216 Staff26 Principal17 Lead20 Manager18 Level TBD56

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64 of 472 matching · page 1 of 2

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Agent infrastructureMid-levelNew

AI Engineer

Booz Allen HamiltonWashington, DC, United States

Posted 1d ago/Full-time/$99k–$225k/yr/Expires Nov 10, 2026

Apply on company site

Why it matters

The role owns production LLM infrastructure spanning RAG, retrieval tuning, evaluation pipelines, observability, guardrails, and agent orchestration patterns including LangGraph and tool calling. It also involves secure deployment and operations for mission-critical federal environments.

About the job

Job Number: R0246911

AI Engineer

The Opportunity

As an AI engineer, you’ll design and deliver production-grade AI systems. You’ll own RAG pipelines, evaluation systems, and performance optimization leveraging modern AI infrastructure and tooling to build scalable, observable, and efficient services. You'll work across the full AI application lifecycle from enterprise data ingestion and retrieval to prompt engineering, evaluation, deployment, observability, and production operations building secure, scalable AI solutions for mission-critical federal environments.

You Have

3+ years of experience building production systems, including AI/ML applications
Experience building LLM systems using RAG frameworks such as LangChain and LlamaIndex, or custom pipelines and vector stores with Pinecone, Weaviate, FAISS, or OpenSearch Vector Search
Experience designing embedding pipelines, including document ingestion, chunking strategies, indexing, metadata filtering, retrieval optimization, and hybrid search, and designing APIs and services using FastAPI, Flask, or Node.js
Experience with cloud-native architectures, including AWS services such as Bedrock, SageMaker, EKS or ECS, S3, IAM, Lambda, CloudWatch, and Secrets Manager, and agent frameworks and orchestration patterns such as LangGraph, tool calling, and function calling APIs
Experience implementing observability, including logging and tracing with OpenTelemetry, Datadog, or CloudWatch, and metrics pipelines tracking latency, throughput, token usage, cache hit rate, and error rates
Experience optimizing performance using caching layers such as Redis, parallelization or async workflows, and chunking and retrieval tuning, and designing automated evaluation pipelines using benchmark datasets, LLM-as-a-judge techniques, regression testing, and human evaluation workflows
Experience supporting production AI services, including deployment, monitoring, incident response, debugging, and performance tuning, and managing prompt templates, prompt versioning, model configurations, and structured outputs across development and production environments
Knowledge of AI security concepts, including prompt injection, jailbreak resistance, data leakage prevention, guardrails, secure prompt design, and responsible AI practices
Ability to obtain a TS/SCI clearance
Bachelor's degree

Nice If You Have

Experience supporting DoD clients or other federal mission environments
Experience with high-performance inference systems such as vLLM, Ray Serve, or Triton Inference Server
Experience with semantic caching and embedding reuse strategies
Experience with guardrail frameworks such as Rebuff, Guardrails.ai, or custom filtering systems
Experience integrating AI applications with enterprise data platforms and knowledge repositories such as Databricks, Snowflake, OpenSearch, PostgreSQL, SharePoint, Confluence, or S3-based document stores
Experience deploying AI workloads into AWS GovCloud, IL4 or IL5 environments, or other secure cloud environments
Experience with event-driven architectures and messaging technologies such as Amazon SQS, Kafka, RabbitMQ, or Amazon EventBridge
Experience with Model Context Protocol (MCP) or modern AI agent interoperability 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 $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, 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.

Stack

langchain
llamaindex
aws
langgraph
opentelemetry
redis
vllm
mcp

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