Cloud Solutions Architect

Booz Allen Hamilton • Fort Bragg, NC

1d

About The Position

As an experienced engineer, you will design, develop, and deliver production-grade agentic AI systems that demonstrate the practical value of generative AI, large language models, and autonomous workflows. The role combines deep technical expertise with product skills to build AI applications using prompting, retrieval-augmented generation (RAG), agentic orchestration, evaluation pipelines, and human-in-the-loop systems to deliver measurable impact.

You will architect modular, reusable AI application patterns; integrate cloud-hosted, local, and hybrid model providers; and apply modern generative AI capabilities such as structured prompting, tool use, workflow orchestration, and multimodal reasoning. You will design solutions for different deployment contexts, optimizing latency, cost efficiency, observability, and safety. You will rapidly prototype and iterate with AI-assisted development tools, using evaluation-driven development and continuous experimentation.

You will help define the direction of mission-critical agentic systems by selecting and combining prompting strategies, RAG architectures, agentic workflows, and fine-tuned or foundation models. You will collaborate with AI and ML engineers, data engineers, data scientists, solutions architects, product owners, and clients to deliver solutions and identify high-value AI opportunities. The role also involves presenting technical solutions, leading workshops and prototyping sessions, and advising on responsible AI practices, ethics, and compliance.

The position requires TS/SCI clearance. The posting does not specify a work location type. Applicants should note that remote roles may occasionally require in-person work at a Booz Allen or customer facility, hybrid roles require facility work in alignment with leadership expectations and role needs, and onsite roles are primarily performed full-time at a customer facility.

Requirements

• At least 2 years of software engineering experience.
• At least 2 years of professional experience in AI- or ML-focused roles.
• Experience with an object-oriented programming language such as Python and applying it to AI or ML solution development.
• Experience designing and implementing production-grade generative or agentic AI applications.
• Experience with RAG architectures, evaluation methodologies, experimentation workflows, and asynchronous or event-driven programming patterns.
• Knowledge of AI data-processing techniques, including text, audio, and multimodal data.
• TS/SCI clearance is required; selected applicants will be subject to a security investigation and may need to meet eligibility requirements for access to classified information.
• Bachelor’s degree.

Nice To Haves

• Experience with agent frameworks, interoperability standards, and multi-agent patterns such as MCP, A2A, LangGraph, or equivalent.
• Experience with model fine-tuning, prompt tuning, domain adaptation, or reinforcement learning from human or AI feedback.
• Experience designing evaluation suites or safety testing frameworks for AI systems.
• Experience integrating AI systems with external tools, APIs, or enterprise systems through tool-calling or computer-use patterns.
• Experience with modern front-end libraries and component-based UI frameworks, including React, and workflows such as build pipelines, automated testing, and code-quality tooling.
• AWS ML, Data Engineer, or Solutions Architect certification.

Responsibilities

• Design adaptable AI architectures supporting multiple model providers, tool ecosystems, modalities, and deployment modes.
• Integrate LLMs, embeddings, RAG pipelines, structured outputs, and long-context or memory mechanisms into production-ready systems.
• Develop data pipelines to ingest, clean, chunk, embed, index, and continuously refresh structured and unstructured data for RAG and memory systems.
• Incorporate guardrails, safety filters, access controls, and monitoring mechanisms for responsible and secure agentic AI deployment.
• Deploy AI services securely and at scale on AWS or equivalent cloud platforms.
• Apply CI/CD and evaluation-driven development practices, including automated testing of prompts and workflows, prompt and agent versioning, and safe model-update rollouts.
• Use AI assistance tools to accelerate development, debugging, and system design while maintaining 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 technical and non-technical stakeholders.
• Lead workshops and prototyping sessions to accelerate adoption.
• Provide guidance on responsible AI practices, ethics, and compliance.

Benefits

• Health, life, and disability benefits.
• Financial and retirement benefits.
• Paid leave.
• Professional development.
• Tuition assistance.
• Work-life programs.
• Dependent care.
• Recognition awards for exceptional performance and demonstration of company values.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level