AI Growth Leader

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

This is an Onsite role based out of Chicago, New York, Dallas, Atlanta .

ROLE OVERVIEW

The AI Growth Leader is a senior commercial leadership role in the Scale Agentic Squad, a global team that helps Capgemini’s clients navigate and lead in the agentic AI era. The role is accountable for originating and winning transformational AI business with strategic clients, and for making sure the first deals turn into rapid, measurable business value.

Working as one team with country, BU, SBU and GBL colleagues, the AI Growth Leader is the single-threaded owner for large AI opportunities (typically €10M+ pipeline, €1M+ contract value). The role owns go-to-market execution for AI Big Bets, orchestrates multi-GBL pursuits and partners, and presents one unified Capgemini AI narrative at CXO level. Each Growth Leader is paired with an AI Solution Leader, who owns solution design and architecture, so that every pursuit combines commercial leadership with technical depth.

KEY RESPONSIBILITIES

Big Bet origination and orchestration

• •Proactively identify, shape and close transformational AI opportunities with strategic and platinum accounts, engaging before formal RFP processes
• •Own end-to-end deal orchestration from opportunity identification through contract signature and handover to delivery
• •Define the integrated offering for each Big Bet with the AI Solution Leader, mapping Capgemini capabilities (e.g. RAISE, AI Factory, data, cloud, sovereign AI) to client objectives
• •Qualify rigorously, focusing effort on winnable, high-value pursuits aligned to the strategic account list

One Capgemini AI narrative

• •Align GTM plays and messaging across I&D, Invent, Cloud and Apps to remove internal competition and client confusion
• •Agree a clear GBL role matrix for each Big Bet and create value propositions that draw on the full Capgemini capability set
• •Build trusted relationships with Chief AI, Data, Technology and Information Officers, working with the CXO Engagement chapter

Partner integration

• •Build joint strategies with Hyperscalers (AWS, Microsoft, Google Cloud), data platforms (Databricks, Snowflake) and AI model partners (Anthropic, OpenAI, Mistral, Google)
• •Secure partner co-investment, co-sell commitments and funding for proof-of-value sprints and demos

Commercial model innovation

• •Drive the shift from time-and-materials and staff augmentation towards outcome-based, fixed-price and managed commercial models
• •Position AI Factory and product-led propositions as transformational partnerships, accelerating deal cycles to 8–12 weeks

Early value realisation

• •Hold executive accountability for the transition from sale to first delivered value, sponsoring the product and forward-deployed engineering teams that deliver first AI solutions
• •Provide ongoing executive sponsorship as solutions scale, expanding point solutions into enterprise-wide programmes
• •Transfer capability to local account and BU teams, so the squad’s direct share falls as the wider business converts

EXPERIENCE AND TECHNICAL KNOWLEDGE

Background

• •Senior commercial leadership in a global systems integrator, hyperscaler professional services, AI-native consultancy, enterprise software vendor with an AI practice, or an AI leadership role in industry
• •A track record of building and scaling AI or data-driven businesses, with large transformational deals originated and closed

Client relationship experience

• •Strategic account leadership with €50M+ total relationship value, and long-term trusted-advisor relationships across multiple engagements
• •C-suite and board-level engagement on AI strategy and business cases (CAIO, CDO, CTO, CIO, CFO)
• •Multi-stakeholder negotiation with procurement, legal and business sponsors

Technical credibility

• •AI and agentic systems: foundation models and LLMs, RAG, fine-tuning, agentic and multi-agent systems, human-in-the-loop design, and what it takes to run AI in production (LLMOps, evaluation, cost and scale)
• •Data and cloud: modern lakehouse and data platforms (Databricks, Snowflake) and hyperscaler AI services (AWS Bedrock and SageMaker, Azure AI Foundry and OpenAI, Google Vertex AI); why the data estate is the constraint on AI value
• •Governance and risk: EU AI Act, GDPR, responsible AI, sovereign AI and AI security (e.g. prompt injection), particularly for regulated industries

Certifications (desirable, not required): hyperscaler AI or architecture credentials (AWS, Azure, Google Cloud), Databricks or Snowflake certifications, and TOGAF, CDMP or PMP/PRINCE2.

LEADERSHIP COMPETENCIES

Success depends on influence without direct authority in a complex, matrixed organisation. The competencies below distinguish high performers.

Competency

What good looks like

Executive presence

Commands the boardroom; adapts fluidly between business, technical and operational audiences; turns scepticism into engagement; represents Capgemini at industry forums.

Strategic vision

Develops ‘think big’ AI strategies and multi-year roadmaps tied to value drivers; balances near-term revenue with long-term account development.

Connects the dots

Translates AI capability into business value (revenue, cost, risk, differentiation); spots dependencies and risks early and addresses them in proposals.

Navigates complexity

Networks rapidly across GBLs, countries and functions; makes progress in ambiguity; aligns stakeholders with different incentives towards one goal.

Originates and facilitates

Creates demand through thought leadership and unsolicited proposals; sets delivery teams up for success through clear scope and stakeholder alignment.

Industry acumen

Deep knowledge of 2–3 priority industries (e.g. FS, MALS, Public Sector, CPRD, EUC); connects horizontal AI to vertical business problems.

Partners with intent

Builds trusted relationships with partner sales and technical teams; creates joint value for clients, partners and Capgemini.

SUCCESS MEASURES

Area

Measures

Commercial performance

Coverage of assigned strategic and platinum accounts

AI bookings value influenced and enabled; win rate uplift; new logo wins (2–3 per year)

Operational excellence

Single-threaded ownership on 100% of Big Bets

Time to first proof of value within 16 weeks

Number and quality of CXO engagements

Strategic impact

Outcome-based and non-T&M deals as a share of portfolio (target 40%+)

Partner co-investment secured on 50%+ of Big Bets

GTM plays and integrated offerings adopted by local teams

WORKING ARRANGEMENTS

Key interfaces

• •AI Solution Leader (two-in-a-box partner) and the wider Scale Agentic Squad, including the AI GTM Scale and CXO Engagement chapters
• •Country AI leaders, BU and Market Unit leadership, and client account teams
• •Strategic Big Deals team (operating within Big Deals governance) and GBL leadership across I&D, Invent, Cloud and Apps
• •Partner organisations: Hyperscalers (AWS, Microsoft, Google Cloud), data platforms (Databricks, Snowflake) and AI model partners (Anthropic, OpenAI, Mistral, Google)

The base compensation range for this role in the posted location is :$200,000-350,000 US/ $200,000-350,000 CA

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 ma