Based in Honolulu, this onsite role at Booz Allen Hamilton offers a comprehensive benefits package and a culture grounded in engineering excellence, collaboration, and responsible AI. You’ll receive health, life, disability, and financial benefits, retirement plans, paid leave, professional development, tuition assistance, work-life programs, dependent care, and a recognition awards program designed to support your well being and growth.
The Opportunity
As an experienced engineer, you will design, build, and deploy production grade agentic AI systems that demonstrate the practical value of generative AI, large language models, and autonomous workflows. You will architect modular patterns that integrate multiple model providers, apply modern GenAI stack capabilities, and deliver solutions that run across cloud and portable builds, optimized for latency, cost, observability, and safety. You will join a broad community of AI and ML engineers, data scientists, solutions architects, and product owners to ship impactful solutions.
Responsibilities
- Design adaptable agentic AI architectures that support multiple model providers, tool ecosystems, modalities, and deployment modes.
- Build modular, reusable components for prompting, retrieval, orchestration, tool execution, memory management, and evaluation to accelerate AI capability development.
- Integrate LLMs, embeddings, RAG pipelines, structured outputs, and long-context or memory mechanisms into production-ready systems.
- Apply advanced prompting techniques (few-shot, chain-of-thought, tool-calling, function-calling) and orchestration frameworks (such as LangChain or equivalents) within agentic architectures (MCP, A2A, or similar) to enable goal-directed autonomy with guardrails, observability, and human oversight, including planning, tool use, delegation, and recovery from failure.
- Design and implement evaluation frameworks offline and online to measure correctness, robustness, safety, and business impact.
- Optimize models and workflows for cost, latency, reliability, and scalability using benchmarking and experimentation.
- Develop data pipelines for ingestion, cleaning, chunking, embedding, indexing, and continuous refresh of structured and unstructured data for RAG and memory systems.
- Combine text, audio, vision, and other modalities in unified processing workflows, including document understanding, transcription, summarization, and cross-modal reasoning.
- Leverage vector databases, hybrid search, reranking, and retrieval optimization to strengthen grounding and reduce hallucination in RAG systems.
- Incorporate guardrails, safety filters, access controls, and monitoring to ensure responsible and secure deployments.
- Deploy AI services securely and at scale on AWS or equivalent cloud platforms.
- Use containerization such as Docker or Kubernetes, or serverless approaches for flexible deployment.
- Apply CI/CD and eval-driven development for AI systems, including automated prompt and workflow testing, versioning of prompts and agents, and safe rollout of model updates.
- Utilize asynchronous programming and event-driven patterns to support scalable, long-running, or multi-agent workflows.
- Adopt modern build and packaging workflows to deliver portable application artifacts.
- Leverage AI assistance tools to accelerate development while upholding engineering rigor and code quality.
- Collaborate with clients to identify high-value AI opportunities and define solution requirements.
- Present AI capabilities and technical solutions to both technical and non-technical stakeholders.
- Lead workshops and prototyping sessions to accelerate adoption and impact.
- Provide guidance on responsible AI practices, ethics, and compliance.
Requirements
- 2+ years of software engineering experience
- 2+ years in AI or ML focused roles in a professional setting
- Experience with an object-oriented language such as Python and applying it to AI/ML solution development
- Experience designing and implementing production grade generative or agentic AI applications
- Experience with AI orchestration frameworks such as LangChain, agent workflows, tool integration, and multi-provider model integration
- Experience with RAG architectures, evaluation methodologies, experimentation workflows, and asynchronous or event-driven programming patterns
- Knowledge of data processing techniques for AI, including text, audio, and multi-modal data
- Ability to obtain a Secret clearance
- Bachelor’s degree in Computer Science or Engineering
Technologies
- Python
- LangChain
- Docker
- Kubernetes
- AWS
- Serverless
- React
- LangGraph
- Cursor
- Windsurf
- Vector databases
- Hybrid search
Work Model
- Onsite: work primarily at a Booz Allen office or customer facility, collaborating with colleagues and clients as required.
- Hybrid: regular presence at a Booz Allen facility with some remote work, aligned with role needs and leadership expectations, with possible visits to customer facilities.
- Remote: listed as remote may include occasional in person work at Booz Allen or customer facilities.
Clearance
Applicants selected will be subject to a security investigation and may need to meet eligibility requirements for access to classified information.
Compensation
Salary range is USD 99,000 to 225,000 per year, commensurate with experience and qualifications.
Identity Statement
As part of the hiring process, you will undergo identity verification using advanced biometrics and AI to ensure authenticity and prevent fraud. You may be asked to be on camera during interviews and assessments, and Booz Allen may take your picture to verify identity.
Candidate AI Usage Policy
AI is a part of Booz Allen’s daily work, and responsible AI use is encouraged. The use of AI or other tools to assist with interview responses is prohibited unless explicit permission is provided.
Commitment to Non-Discrimination
All qualified applicants will receive consideration for employment without regard to disability, veteran status, or any other status protected by law.
