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 Lead, you will work directly with clients and multidisciplinary delivery teams to turn complex business and mission needs into practical, production-ready AI solutions. You will operate at the intersection of AI, software engineering, data, and client delivery, moving quickly from ambiguous problems to working prototypes, integrated solutions, and scalable implementation patterns. This role combines hands-on engineering, client-facing technical leadership, innovation, and team development. You will lead complex forward deployed engagements while helping build the next generation of Forward Deployed Engineers through hands-on mentorship, technical coaching, and repeatable engineering and delivery best practices.
Forward Deployed Engineering & Solution Delivery
- Lead forward deployed engineering engagements, partnering directly with clients to understand complex workflows, identify high-value opportunities, and translate business and mission needs into working AI solutions.
- Rapidly design, prototype, test, and deploy generative AI and agentic AI applications within complex enterprise environments.
- Build advanced AI solutions using leading large language models, APIs, developer tooling, and enterprise AI platforms.
- Translate ambiguous and evolving requirements into practical technical designs, prototypes, and production-ready solutions.
- Design and implement agentic architectures incorporating Model Context Protocol (MCP), agent-to-agent (A2A) communication, retrieval-augmented generation (RAG), tool use, structured outputs, orchestration, context management, and human review where appropriate.
- Lead technical discovery sessions, architecture discussions, demonstrations, and hands-on solution working sessions with client stakeholders.
- Partner directly with users throughout implementation to gather feedback, diagnose challenges, refine solutions, and drive adoption.
- Identify innovative and practical ways to apply emerging AI capabilities to complex client challenges while balancing usability, performance, security, maintainability, and responsible AI.
Engineering & Integration
- Architect, build, and maintain integrations with internal and external systems using APIs, services, data pipelines, and modern application development practices.
- Design AI applications and agents that interact with enterprise data, tools, business systems, APIs, and other agents.
- Design and implement MCP-based integrations connecting AI applications and agents with enterprise tools, services, and data sources.
- Design and implement A2A and multi-agent patterns enabling specialized agents to coordinate and communicate as part of broader workflows.
- Design and implement RAG solutions, including enterprise knowledge retrieval, embeddings, vector search, grounding, and related retrieval patterns.
- Apply modern software engineering practices to move solutions from rapid prototype through testing, deployment, and operational support.
- Work with relational databases, vector stores, retrieval systems, APIs, and related data patterns to support application state, knowledge retrieval, traceability, and auditability.
- Implement testing, evaluation, logging, monitoring, and observability for AI-enabled applications and agentic workflows.
- Diagnose complex technical and integration issues across applications, models, agents, APIs, data, and infrastructure.
- Establish reusable technical patterns and accelerators that improve the quality and speed of future implementations.
Client & Technical Leadership
- Serve as a trusted senior technical advisor to clients on complex generative AI and agentic AI initiatives.
- Build relationships with technical, business, data, and leadership stakeholders, connecting client needs with practical technical solutions.
- Communicate complex technical concepts, solution options, risks, and trade-offs clearly to technical teams, business stakeholders, and senior client leaders.
- Facilitate technical discovery and working sessions that turn ambiguous client problems into actionable engineering decisions and solution approaches.
- Present prototypes, solution demonstrations, architecture decisions, and technical recommendations to client stakeholders.
- Ask effective questions, listen to client needs, and adapt technical approaches based on business, mission, user, and technology considerations.
- Challenge assumptions constructively and propose innovative approaches when conventional solutions do not adequately address the problem.
- Balance rapid experimentation and creative problem-solving with the engineering discipline required to deliver reliable, secure, maintainable, and scalable solutions.
FDE Capability Building & Mentorship
- Mentor and develop junior and mid-level engineers into effective Forward Deployed Engineers, building both their technical engineering skills and client-facing delivery capabilities.
- Coach team members on FDE best practices, including technical discovery, problem decomposition, requirements translation, rapid prototyping, solution design, client communication, demonstrations, implementation, troubleshooting, and knowledge transfer.
- Provide hands-on technical direction, architecture guidance, code review, pairing, and engineering mentorship.
- Develop and promote reusable FDE playbooks, engineering standards, solution patterns, accelerators, and implementation best practices.
- Coach team members on modern agentic AI engineering patterns, including MCP, A2A, RAG, tool use, orchestration, evaluation, and responsible AI practices.
- Help engineers become comfortable operating in ambiguous client environments and moving independently from problem identification through working solution.
- Create opportunities for junior team members to progressively assume responsibility for technical discovery, client discussions, demonstrations, solution ownership, and technical leadership.
- Foster a culture of experimentation, continuous learning, collaboration, technical excellence, and responsible AI development.
- Capture and share lessons learned across engagements to continuously improve FDE practices and delivery quality.
What You Will Need:
- Must be able to OBTAIN and MAINTAIN a Federal PUBLIC TRUST;. Candidates with an ACTIVE PUBLIC TRUST or SUITABILITY are preferred.
- SEVEN (7+) or more years of overall work experience.
- Experience in software engineering, data engineering, AI/ML engineering, solution engineering, or a related technical role.
- Experience working as a Forward Deployed Engineer, Forward Deployed Software Engineer, Forward Deployed AI Engineer, or in a comparable client-embedded engineering role, including translating ambiguous client requirements into working technical solutions.
- Hands-on experience designing and 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 connecting AI applications or agents with tools, services, data sources, or enterprise systems.
- Hands-on experience with agent-to-agent (A2A) and multi-agent solution patterns, including communication or coordination among specialized agents.
- Hands-on experience designing and implementing retrieval-augmented generation (RAG) solutions, including enterprise knowledge retrieval, embeddings, vector search, and grounding LLM applications with authoritative data or content.
- Hands-on experience designing agentic AI solutions using tool use, structured outputs, context management, orchestration, and human-in-the-loop patterns.
- Strong software engineering experience using modern programming languages, APIs, services, and application development frameworks.
- Experience integrating AI applications and agents with enterprise systems, databases, APIs, tools, and data sources.
- Experience developing reliable, maintainable, testable, and well-documented production code.
- Demonstrated experience mentoring and developing engineers, including coaching team members on engineering standards, technical problem-solving, solution delivery, and client-facing responsibilities.
- Strong client communication and consulting skills, with demonstrated ability to work effectively with technical teams, business stakeholders, and senior client leaders.
- Demonstrated ability to lead technical discovery and translate ambiguous business or mission problems into actionable technical requirements and working solutions.
- Demonstrated experience leading complex technical implementations and providing technical direction to engineering or multidisciplinary teams.
- Demonstrated ability to think innovatively, challenge conventional approaches, rapidly evaluate emerging technologies, and develop creative technical solutions to complex or undefined problems.
- Strong written, verbal, presentation, facilitation, and interpersonal communication skills, including the ability to communicate technical concepts, architecture decisions, risks, recommendations, and trade-offs to technical and non-technical audiences.
What Would Be Nice To Have:
- Bachelor’s degree from an accredited university.
- Master’s degree in Computer Science, Engineering, Data Science, Artificial Intelligence, or a related technical field.
- Experience delivering AI, data, or software solutions within Federal Government, healthcare, financial services, or other highly regulated environments.
- Experience deploying generative AI and agentic solutions on major cloud and enterprise AI platforms such as Microsoft Azure / Azure OpenAI, AWS / Amazon Bedrock, Google Cloud / Vertex AI, Databricks, or comparable platforms.
- Experience with modern AI and agent development frameworks and patterns, such as LangGraph, LangChain, Semantic Kernel, or comparable orchestration frameworks.
- Experience operationalizing generative AI solutions, including LLM evaluation, tracing, observability, prompt and model management, guardrails, cost optimization, and production monitoring.
- Experience designing secure AI architectures incorporating identity and access management, secrets management, API security, data protection, authorization, auditability, and responsible AI controls.
- Experience working with containers, CI/CD pipelines, infrastructure-as-code, and cloud-native deployment patterns, including technologies such as Docker, Kubernetes, GitHub Actions, Azure DevOps, or Terraform.
- Experience with knowledge graphs, graph databases, advanced retrieval techniques, hybrid search, reranking, or other approaches that improve the quality and reliability of enterprise RAG solutions.
- Experience developing reusable AI accelerators, reference architectures, engineering frameworks, or platform capabilities that can be applied across multiple teams or client engagements.
- Experience contributing to technical strategy, solution architecture, estimation, proposal development, technical demonstrations, or client pursuit activities.
- Relevant cloud, AI, data, or security certifications.
- Active Federal Public Trust, Secret, or higher-level security clearance.
The annual salary range for this position is $149,000.00-$248,000.00. Compensation decisions depend on a wide range of factors, including but not limited to skill sets, experience and training, security clearances, licensure and certifications, and other business and organizational needs.
What We Offer:
Guidehouse offers a comprehensive, total rewards package that includes competitive compensation and a flexible benefits package that reflects our commitment to creating a diverse and supportive workplace.
Benefits include:
- Medical, Rx, Dental & Vision Insurance
- Personal and Family Sick Time & Company Paid Holidays
- Position may be eligible for a discretionary variable incentive bonus
- Parental Leave and Adoption Assistance
- 401(k) Retirement Plan
- Basic Life & Supplemental Life
- Health Savings Account, Dental/Vision & Dependent Care Flexible Spending Accounts
- Short-Term & Long-Term Disability
- Student Loan PayDown
- Tuition Reimbursement, Personal Development & Learning Opportunities
- Skills Development & Certifications
- Employee Referral Program
- Corporate Sponsored Events & Community Outreach
- Emergency Back-Up Childcare Program
- Mobility Stipend
About Guidehouse Guidehouse is an Equal Opportunity Employer–Protected Veterans, Individuals with Disabilities or any other basis protected by law, ordinance, or regulation.
Guidehouse will consider for employment qualified applicants with criminal histories in a manner consistent with the requirements of applicable law or ordinance including the Fair Chance Ordinance of Los Angeles and San Francisco.
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