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# Cloud Solutions Architect

- **Company:** Booz Allen Hamilton Inc.
- **Location:** Fayetteville, NC, United States
- **Experience:** Experienced
- **Salary:** $99,000 - $225,000
- **Contract:** Permanent contract
- **Skills:** LangGraph Framework, Application Programming Interfaces (APIs), Artificial Intelligence, Amazon Web Services, Automation of Tests, Software Quality, Continuous Integration, Software Debugging, Event-Driven Programming, Design of User Interfaces, Interoperability, Python (Programming Language), Object-Oriented Software Development, Cloud Services, Systems Integration, Unstructured Data, Management of Software Versions, Reinforcement Learning, Data Processing, ReactJS, Evaluation Pipelines, Retrieval-Augmented Generation, Transfer Learning, Delivery Pipeline, Large Language Models, Multi-Agent Systems, Generative AI, Agentic-AI, AI Platforms, Virtual Agents, Data Pipelines, Human in the Loop, Agent2Agent Protocol
- **Published:** November 7, 2026
- **Apply:** https://www.dice.com/job-detail/cc5dc8df-edda-43e1-ad4b-34c75915ba24

## About the Role

* 2+ years of experience with sof tware engineering
 * 2+ years of experience in AI or ML-focused roles in a professional environment
 * 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 met hodologies, experimentation workflows, and asynchronous or event-driven programming patterns
 * Knowledge of data processing techniques for AI, including text, audio, and multi-modal
 * TS/SCI clearance
 * Bachelor's degree

Nice If You Have:

 * 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, and integrating AI systems with external tools, APIs, or enterprise systems via tool-calling or computer-use patterns
 * Experience with modern front-end libraries and frameworks for component-based UI development, including React, and workflows such as build pipelines, automated testing, and code quality tooling
 * AWS ML, Data Engineer, or Solutions Architect Certification

## Description

As an experience d engineer, you know how to design, develop, and deliver production-grade agentic AI systems that demonstrate the practical value of generative AI, large language models ( LLMs ) , and autonomous workflows. This role combines deep technical expertise with strong product skills to design AI applications that leverage 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 multiple model providers such as cloud-hosted, local, and hybrid , and apply modern GenAI stack capabilities, including structured prompting, tool use, workflow orchestration, and multi-modal reasoning. You will design solutions deployable across various contexts, from cloud-hosted platforms to portable, self-contained builds, optimizing for latency, cost efficiency, observability, and safety. You will rapidly prototype and iterate using AI-assisted development tools, validating hypotheses through evaluation-driven development and continuous experimentation.

In this role, you'll define the direction of mission-critical agentic systems by selecting and combining prompting strategies, RAG architectures, agentic workflows, and fine-tuned or foundation models as appropriate. You'll be part of a large community of AI and ML engineers across the company, collaborating with data engineers, data scientists, solutions architects, and product owners to deliver world-class solutions.

What You'll Work On:

 * Design adaptable AI architectures that support 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 for ingestion, cleaning, chunking, embedding, indexing, and continuous refresh of structured and unstructured data for RAG and memory systems.
 * Incorporate guardrails, safety filters, access controls, and monitoring mechanisms to ensure responsible and secure deployment of agentic AI systems.
 * Deploy AI services securely and at scale on AWS or equivalent cloud platforms.
 * Apply CI / CD and evaluation-driven development best practices for AI systems, including automated testing of prompts and workflows, versioning of prompts and agents, and safe rollout of model updates.
 * 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 both technical and non-technical stakeholders.
 * Lead workshops and prototyping sessions to accelerate adoption.
 * Provide guidance on responsible AI practices, ethics, and compliance.