# Forward Deployed AI Engineer Source: https://realanalystjobs.com/job/forward-deployed-ai-engineer-guidehouse-a17c3636 Forward Deployed AI Engineer at Guidehouse, an on-site role based in McLean, Virginia, USA. Posted on 10 November 2026, read from Guidehouse's own careers page (Workday), which RealAnalystJobs re-checks daily and removes the role when it closes. Guidehouse has approved H-1B petitions on USCIS record (employer-wide, not a promise for this role). Updated 15 November 2026. ## Key facts - Company: [Guidehouse](https://realanalystjobs.com/companies/guidehouse) - Location: McLean, Virginia, USA - Work mode: On-site - Posted: Nov 10, 2026 - Employment type: Full time - Source: Guidehouse's careers page (Workday), re-checked daily Skills: Azure ## Visa sponsorship The posting does not say. Guidehouse had H-1B petitions approved for 57 workers in fiscal year 2026 (USCIS). That is history, not a promise for this role. [See the record](https://realanalystjobs.com/companies/guidehouse#h1b-record) ## About this role Job Family : Data Science Consulting Travel Required : Up to 10% Clearance Required : Ability to Obtain Public Trust What You Will Do : As a Forward Deployed AI Engineer , you will work directly with clients, technical leads, and multidisciplinary delivery teams to turn complex business and mission needs into practical AI solutions. You will combine hands-on software engineering, generative and agentic AI development, problem-solving, and client interaction to rapidly prototype, build, integrate, test, and improve solutions in real-world environments. You will work alongside senior Forward Deployed Engineers and technical leads while developing deeper expertise in forward deployed engineering practices and client delivery. Forward Deployed Engineering & Solution Delivery • Work directly with clients and technical leads to understand workflows, technical challenges, user needs, and opportunities for applying AI. • Translate business, mission, and user requirements into technical designs, prototypes, and working solutions. • Design, prototype, test, and deploy generative AI and agentic AI applications in enterprise environments. • Build AI solutions using large language models, APIs, developer tooling, enterprise data, and modern application development practices. • Develop agentic solutions incorporating Model Context Protocol (MCP), agent-to-agent (A2A) communication, retrieval-augmented generation (RAG), tool use, structured outputs, context management, orchestration, and human-in-the-loop patterns . • Participate in client discovery sessions, technical working sessions, demonstrations, and solution design discussions. • Gather feedback from users and stakeholders and rapidly incorporate that feedback into working solutions. • Troubleshoot technical issues and collaborate with client and delivery teams to identify practical solutions. • Explore emerging AI technologies and identify innovative ways to apply them to real-world business and mission problems. Engineering & Integration • Build and maintain integrations with enterprise systems, services, APIs, databases, data sources, and workflow tools. • Develop AI applications and agents that interact with enterprise data, tools, systems, APIs, and other agents. • Build MCP-based integrations connecting AI applications and agents with tools, services, enterprise systems, and data sources. • Implement A2A and multi-agent patterns supporting communication and coordination among specialized agents. • Build RAG solutions , including knowledge retrieval, embeddings, vector search, grounding, and integration with enterprise content and data. • Develop agentic workflows using tool use, structured outputs, context management, orchestration, and human review where appropriate. • Apply modern software engineering practices to develop reliable, maintainable, testable, and well-documented solutions. • Work with relational databases, vector stores, APIs, and other data storage and retrieval technologies. • Support testing, evaluation, logging, monitoring, and troubleshooting of AI-enabled applications and agentic workflows. • Participate in code reviews, technical design reviews, and other engineering quality practices. Client Delivery & Problem Solving • Communicate effectively with technical and non-technical client stakeholders. • Ask effective questions to understand client problems, workflows, constraints, and desired outcomes. • Explain technical concepts, prototypes, and solution approaches clearly to client stakeholders. • Participate in client demonstrations, technical discovery, and working sessions. • Work effectively in environments where requirements may be ambiguous, evolving, or initially undefined. • Apply creative and analytical thinking to break complex problems into manageable technical solutions. • Rapidly evaluate new technologies, patterns, and approaches and determine how they may apply to client needs. • Collaborate with senior engineers and client stakeholders to evaluate technical options, risks, and trade-offs. • Incorporate client and user feedback into solution design and implementation. FDE Development & Collaboration • Work with senior Forward Deployed Engineers and technical leads to develop strong FDE skills and delivery practices. • Apply FDE best practices related to discovery, problem decomposition, requirements translation, rapid prototyping, solution design, implementation, testing, demonstrations, and knowledge transfer. • Participate in pair programming, code reviews, architecture discussions, and technical learning activities. • Contribute reusable code, technical patterns, accelerators, documentation, and lessons learned to improve future implementations. • Share knowledge with other engineers and contribute to a collaborative engineering culture. • Demonstrate curiosity and a willingness to rapidly learn new AI technologies, engineering patterns, client domains, and business processes. What You Will Need: • Must be able to OBTAIN and MAINTAIN a Federal PUBLIC TRUST; candidates must obtain approved adjudication of their PUBLIC TRUST prior to onboarding with Guidehouse. Candidates with an ACTIVE PUBLIC TRUST or SUITABILITY are preferred. • THREE (3+) or more years of overall work experience. • Experience in software engineering, AI/ML engineering, data engineering, solution engineering, or a related technical role. • Experience performing forward deployed engineering or comparable client-facing technical delivery, including working directly with users or clients to translate business or mission needs into working technical solutions. • Hands-on experience building generative AI, large language model, or agentic AI solutions. • Hands-on experience developing solutions using Claude APIs, Claude for Enterprise, Claude Code, tool use, Custom Skills, or comparable enterprise large language model platforms and developer tooling. • Hands-on experience with Model Context Protocol (MCP) and its use in conn Description from Guidehouse's public careers feed, reproduced so you can read the role here. Apply on the company's own site; Real Analyst Jobs never submits anything for you. ## How to apply Open [this role on Real Analyst Jobs](https://realanalystjobs.com/job/forward-deployed-ai-engineer-guidehouse-a17c3636) and use Apply now there to reach the employer's application. The listing is re-checked against Guidehouse's careers page daily and removed when it closes. ## Guidehouse 65 open analyst roles on Real Analyst Jobs. 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