AI Transformation & Delivery Manager

Choosing Capgemini means choosing a company where you will be empowered to shape your career in the way you’d like, where you’ll be supported and inspired by a collaborative community of colleagues around the world, and where you’ll be able to reimagine what’s possible. Join us and help the world’s leading organizations unlock the value of technology and build a more sustainable, more inclusive world.

Location

Seattle WA

Your Role

Capgemini is seeking a senior AI leader to help scale its Seattle-based AI & Analytics team and support a growing portfolio of strategic engagements and pursuits across Microsoft and other major local accounts. This is not a traditional individual-contributor Data Scientist role. The position combines enterprise AI architecture, hands-on technical credibility, client delivery, business development, account collaboration, and people leadership.

The successful candidate will operate as a trusted partner to clients, Capgemini account teams, Insights & Data go-to-market leaders, and AI&A leadership. The role will help shape opportunities, mobilize delivery teams, guide enterprise-grade AI solutions from idea through production, and mentor a growing team of early-career and experienced practitioners.

• •Expand Capgemini’s AI presence in the Seattle market by connecting technical capability to credible client opportunities and measurable business outcomes.
• •Provide day-to-day leadership capacity for the Seattle AI&A team, including staffing, coaching, skills development, quality oversight, and team engagement.
• •Convert AI concepts and prototypes into secure, governed, production-ready solutions and reusable enterprise capabilities.
• •Build strong working relationships across clients, account teams, go-to-market leaders, partners, and AI&A leadership while maintaining clear ownership and follow-through.
• •Balance hands-on technical depth with practical consulting judgment, commercial awareness, and delivery realism.

• •Lead discovery and executive working sessions to frame business problems, prioritize AI use cases, define value hypotheses, and create phased transformation roadmaps.
• •Architect enterprise AI solutions spanning predictive AI, Generative AI, intelligent applications, Agentic AI, conversational and multimodal experiences, and AI-assisted software engineering.
• •Design platform capabilities such as model and agent gateways, orchestration, tool and API integration, data and semantic layers, identity and access, evaluation, observability, FinOps, and lifecycle management.
• •Establish practical governance-by-design patterns covering Responsible AI, security, privacy, human oversight, agent identity and authorization, traceability, auditability, testing, and runtime controls.
• •Guide cloud and platform choices across Azure and Microsoft technologies, while remaining credible across AWS, GCP, Databricks, Snowflake, and relevant partner ecosystems.

• •Provide architecture and engineering leadership from pursuit and proof of value through production deployment, adoption, and operational support.
• •Remain sufficiently hands-on to review code, prototypes, prompts, agent workflows, APIs, retrieval pipelines, data flows, evaluations, deployment patterns, and technical trade-offs.
• •Lead or support Forward Deployment Engineer / Hyper Velocity Engineering-style engagements requiring close client collaboration, rapid iteration, and ownership of business outcomes.
• •Define engineering standards for reliability, security, testing, CI/CD, LLMOps/MLOps, monitoring, incident response, and production readiness.
• •Identify delivery risks early, shape realistic staffing and work plans, and ensure quality across mixed onshore, nearshore, and offshore teams.

Required Skills and Experience

10+ years of experience in technology consulting, enterprise architecture, data/AI, software engineering, product management, product engineering, or related fields, including meaningful leadership responsibility.

• •Demonstrated experience shaping and delivering enterprise AI solutions beyond experimentation, including GenAI and/or Agentic AI solutions integrated with business processes and systems.
• •Strong architecture knowledge across applications, APIs, data, cloud, security, integration, identity, deployment, and operations.
• •Hands-on working knowledge of Python and SQL, plus the ability to review modern AI application code, notebooks, API integrations, source repositories, and deployment configurations.
• •Experience with LLM application patterns such as RAG, agent and tool orchestration, function calling, structured outputs, evaluation, guardrails, prompt and context engineering, and human-in-the-loop workflows.
• •Experience with cloud AI services and modern data platforms. Strong Azure/Microsoft experience is preferred; credible AWS, GCP, Databricks, or Snowflake experience is also valuable.
• •Experience leading client-facing consulting engagements, solution architecture, technical delivery, or transformation programs involving senior business and technology stakeholders.
• •Business development experience including opportunity shaping, proposal development, estimation, executive storytelling, workshops, demonstrations, or RFP responses.
• •People-management or sustained team-lead experience, with evidence of mentoring, coaching, staffing, developing, and caring for team members.
• •Excellent written and verbal communication, structured problem solving, executive presence, and ability to explain technical trade-offs to non-technical audiences.
• •Ability to work regularly from the Bellevue/Seattle area and engage at local client sites when needed.
• •Experience with Azure AI Foundry, Azure OpenAI, Microsoft Copilot Studio, Microsoft Fabric, Azure AI Search, Azure API Management, Microsoft Entra, Azure DevOps, GitHub, and Microsoft-aligned agent or application platforms.
• •Experience with frameworks and protocols such as MCP, agent-to-agent integration, LangGraph, LangChain, AutoGen, or equivalent orchestration technologies.
• •Knowledge of LLMOps/MLOps, model and agent evaluation, observability, red teaming, content safety, AI security, cost optimization, and production operations.
• •Experience designing enterprise AI platforms, AI control planes, model/agent gateways, reusable agent services, semantic layers, knowledge platforms, or governed self-service capabilities.
• •Experience in one or more locally relevant industries such as technology, retail/consumer products, telecommunications, aerospace/manufacturing, travel/hospitality, or utilities.
• •Relevant cloud, architecture, data, AI, security, or Microsoft certifications. Forward-deployed engineering, HVE/FTE, or similar client-proximate delivery experience is a plus

Education

Bachelor’s degree Computer Science, Engineering, Data Science, Artificial Intelligence, Information Systems, or a related discipline, or equivalent professional experience. An advanced technical or business degree is a plus.

The base compensation range for this role in the posted location is $ 109,180 to $197,175

Capgemini provides compensation range information in accordance with applicable national, state, provincial, and local pay transparency laws. The base compensation range listed for this position reflects the minimum and maximum target compensation Capgemini, in good faith, believes it may pay for the role at the time of this posting. This range may be subject to change as permitted by law.

The actual compensation offered to any candidate may fall outside of the posted range and will be determined based on multiple factors legally permitted in the applicable jurisdiction.

These may include, but are not limited to: Geographic location, Education and qualifications, Certifications and licenses, Relevant experience and skills, Seniority and performance, Market and business consideration, Internal pay equity.

It is not typical for candidates to be hired at or nea