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Guidehouse

Advises agencies and runs regulated operations

Forward Deployed AI Engineer

AI Application EngineeringPosted on Nov 10
Full-time

About the Job

Requirements

  • Must be able to obtain and maintain a Federal Public Trust, with approved adjudication before onboarding; candidates with an active Public Trust or suitability are preferred.
  • At least three 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, 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) to connect AI applications or agents with tools, services, data sources, or enterprise systems.
  • Experience with agent-to-agent (A2A) or multi-agent solution patterns, including communication or coordination among multiple agents.
  • Hands-on experience developing retrieval-augmented generation (RAG) solutions, including retrieval, embeddings, vector search, and grounding large language model applications with enterprise data or content.
  • Experience developing agentic workflows incorporating tool use, structured outputs, context management, orchestration, and human-in-the-loop patterns.
  • Strong software development skills using modern programming languages, APIs, services, and application development frameworks.
  • Experience integrating applications with APIs, databases, data sources, or enterprise systems.
  • Understanding of modern software engineering practices, including source control, testing, debugging, code review, documentation, and maintainable code development.
  • Strong client communication and interpersonal skills, including the ability to explain technical concepts to technical and non-technical audiences.
  • Ability to work effectively with clients and multidisciplinary teams where requirements are evolving or ambiguous.
  • Demonstrated curiosity, innovative thinking, creative problem-solving, and ability to learn and apply new technologies quickly.
  • Strong written and verbal communication skills.
  • U.S. citizenship is contractually required.

Responsibilities

  • 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, agent-to-agent communication, retrieval-augmented generation, 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 it into working solutions.
  • Troubleshoot technical issues and collaborate with client and delivery teams to identify practical solutions.
  • Explore emerging AI technologies and identify ways to apply them to real-world business and mission problems.
  • 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 Model Context Protocol-based integrations connecting AI applications and agents with tools, services, enterprise systems, and data sources.
  • Implement agent-to-agent and multi-agent patterns supporting communication and coordination among specialized agents.
  • Build retrieval-augmented generation 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.
  • Communicate with technical and non-technical client stakeholders; ask questions to understand client problems, workflows, constraints, and desired outcomes; and explain technical concepts, prototypes, and solution approaches clearly.
  • Participate in client demonstrations, technical discovery, and working sessions.
  • Work effectively 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.
  • Work with senior Forward Deployed Engineers and technical leads to develop forward deployed engineering skills and delivery practices.
  • Apply forward deployed engineering best practices for 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.
  • Learn new AI technologies, engineering patterns, client domains, and business processes.

Desired Qualifications

  • Prior experience as a Forward Deployed Engineer, Forward Deployed Software Engineer, Forward Deployed AI Engineer, or in a similar client-embedded engineering role.
  • Additional hands-on experience developing Claude-based solutions, including Claude Code, API development, tool use, Custom Skills, or Model Context Protocol.
  • Anthropic Academy coursework or certificates in AI Fluency, API development, Model Context Protocol, Claude Code, or related platform topics.
  • Anthropic partner training or certification experience, or equivalent platform-focused training.
  • Experience building end-to-end agentic AI applications from prototype through implementation.
  • Experience testing and evaluating generative AI or agentic AI systems, including validation, quality review, or regression testing.
  • Experience with relational databases, data modeling, vector databases, or modern data platforms.
  • Experience with cloud environments such as AWS, Microsoft Azure, or Google Cloud.
  • Familiarity with AI safety, security, privacy, governance, and responsible AI practices.
  • Experience with logging, monitoring, tracing, or observability for applications or AI-enabled systems.
  • Experience delivering technology solutions in federal, regulated, or other complex enterprise environments.
  • Experience delivering technology, data, AI, or digital solutions in healthcare, life sciences, public health, or other health-related environments.
  • Familiarity with regulated health environments and considerations related to data privacy, security, governance, and responsible use of AI.
  • Interest in continuing to develop expertise in forward deployed engineering, agentic AI, and client-facing technical delivery.
  • A bachelor's degree from an accredited university.

About the Company

Guidehouse

Advises agencies and runs regulated operations

Guidehouse advises government agencies and companies in regulated industries on strategy, technology and day-to-day operations. Its work combines business advice with software implementation and ongoing management, so a client uses the same firm to plan a change, build the systems and run the resulting processes. Teams modernize cloud platforms, apply data analysis and artificial intelligence, and redesign organizations to meet operating and regulatory requirements. Clients pay for consulting projects and technology work or outsource continuing business functions to its managed services teams. Guidehouse was founded in 2018 and is headquartered in McLean, Virginia.

Company size
10,001+
Company stage
Acquired
Total funding
$750K
Headquarters
McLean, VA
Founded
2018

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