Principal Solution Architect (Agentic AI, GenAI, Custom Development)

Your role

As a Principal Solution Architect, you define how we design, position, and deliver AI‑powered and custom-built solutions across our most strategic engagements. You act as a trusted advisor to clients and internal stakeholders, shaping opportunities from early qualification through deal closure into successful delivery. With Agentic AI and GenAI at the core, you translate complex, ambiguous business challenges into scalable, enterprise‑grade architectures across cloud and on‑prem environments. You lead the technical narrative in bids, RFPs, executive discussions, and client workshops, influencing both solution design and commercial strategy. Beyond individual deals, you help shape Capgemini’s AI and custom development offerings — creating reference architectures, reusable assets, and go‑to‑market propositions. This role offers real ownership, strong exposure to senior client stakeholders, and direct impact on how we build and grow our AI business.

Your tasks

• Lead solutioning and win strategic AI and custom development engagements — drive the technical narrative, define approach and architecture, and actively participate in proposal defence with clients.
• Shape commercially viable solutions — define scope, architecture, delivery approach, effort estimates, risks, and pricing assumptions in collaboration with sales and delivery teams.
• Design end-to-end enterprise architectures combining LLMs, agentic patterns, and RAG — including integration with existing systems, data flows, security, scalability, observability, and cost optimization.
• Ensure enterprise-grade AI governance — define guardrails, support model evaluation approach, and address compliance, security, and operational risks early in the solution design.
• Build and evolve GenAI offerings and reusable assets — contribute to reference architectures, reusable components (e.g. RAG patterns, accelerators), and help standardize delivery approaches.
• Lead client-facing activities — run workshops, support discovery phases, structure requirements, and translate business problems into architecture proposals and roadmaps.
• Contribute to broader custom development initiatives — support solutioning for modernization, cloud-native builds, and integrations, identifying where AI brings tangible value.
• Act as a trusted technical advisor — support clients across pre-sales and early delivery phases, and mentor architects and senior engineers through reviews, feedback, and hands-on guidance.

Your profile

• 10+ years of experience in software engineering and architecture, including several years in a client-facing solutioning, pre-sales, or principal architect role.
• Proven track record of winning and delivering complex, high-value engagements — you have directly shaped solutions, led proposal defence, and influenced client decisions in competitive scenarios.
• Strong, hands-on experience in AI / GenAI — including practical use of LLMs, RAG patterns, and agentic workflows in production or near-production environments (not only PoCs).
• Solid architectural background in enterprise software systems — with proven ability to design distributed, scalable solutions and integrate AI components into existing application landscapes.
• Experience in cloud-native and hybrid architectures across Azure, AWS, or GCP — including containers, Kubernetes, CI/CD, security, and cost management, ideally with exposure to AI/ML workloads.
• Real experience in bids and commercial shaping — including defining scope, estimating effort, identifying risks, and contributing to pricing and commercial assumptions.
• Comfortable working at the intersection of business and technology — able to structure vague problems, push back when needed, and translate business needs into actionable architecture decisions.
• Strong stakeholder management skills — able to engage both senior business stakeholders and engineering teams, and translate between both worlds.
• Fluent English (C1+) with the ability to work in client-facing and proposal contexts.

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