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Shape AI reinvention strategy for client CTO, CFO, and CISO: build value architecture, ROI backlogs, use case prioritisation frameworks, and multi-year AI adoption roadmaps; engage CPOs and Chief Procurement Officers on AI-enabled procurement transformation strategies, connecting cost-out objectives to scalable AI architectures. Key Responsibilities: Lead enterprise AI platform deployments across complex multi-stakeholder client environments - Anthropic, OpenAI, Microsoft, Google, Salesforce, SAP, or Palantir - owning the full programme from architecture through adoption, including Sourcing & Procurement platforms such as SAP Ariba, Coupa, Ivalua, or Jaggaer.

Accenture Plc

Sourcing and Procurement Data & AI Senior Manager

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Google's Gemini Enterprise for Customer Experience (GECX) is changing what's possible: intelligent agents that handle complex customer interactions autonomously, real-time insights that transform how companies understand their customers, and commerce experiences that feel personal at scale. We are the Accenture Google Business Group (AGBG) Mid-Market team-a specialized group of engineers, architects, and builders delivering tailored Google Cloud solutions for mid-market, high-growth, and fast-paced enterprises.

Field CTO - Customer Engagement Solutions, Google Cloud

Drive practice performance: Own annual bookings and revenue attainment, and track practice-sourced and influenced pipeline, conversion, win rate, Marketplace activity, utilization, margin, time to value, solution reuse, model quality, adoption, customer references, thought-leadership reach, certification progress, customer satisfaction, and measurable business outcomes. Own bookings and revenue growth: Carry direct accountability for $50M-$100M in annual practice bookings and revenue, partner with sales leaders and AWS field teams to originate opportunities, qualify use cases, shape value propositions, and convert discovery sessions, data assessments, and proofs of value into production Data and AI pipeline.

Accenture Edge for AWS Tech Practice Leader - Data and AI

Key Responsibilities: Utilize relevant AI tools across all tasks and deliverable creation, including the creation of low-code proof of concepts (POCs), agents and other artifacts that facilitate: Be able to analyze client's current state by assessing processes, technology tools and organizational structure with an intent to transform to a data and AI insight driven future state. We work with our pharmaceutical, biotech, medical technology, distributor and consumer health clients globally to redefine the future of the life sciences industry: combining the latest technology with scientific breakthroughs to revolutionize how medical treatments are discovered, developed and delivered to patients around the world.

Digital Manufacturing Transformation Consultant | Life Sciences

You are a trusted advisor to clients, Microsoft leadership, and Accenture account teams, bringing deep expertise across Microsoft technologies including CoPilot, Microsoft Fabric, Agent365, Microsoft Azure and other Microsoft offerings. As the Microsoft Ecosystem Business Development Director, you are responsible for driving strategic growth across Accenture's Microsoft business by originating, shaping, and advancing opportunities centered on Microsoft's AI, Data, Customer Experience, Security, and Industry platforms.

Microsoft Ecosystem Business Development Director

We are Secure, Responsible AI & Data Protection professionals who enable trust, resilience, and compliance across the AI lifecycle and data estate; including securing AI systems and agents against emerging threats like prompt injection, model manipulation, and unauthorized agent actions, applying AI to strengthen cyber defense through faster detection, triage, and response, and protecting sensitive data through classification, data loss prevention, and governed access, so that enterprises can adopt AI and agentic capabilities confidently while safeguarding data and meeting their regulatory obligations. Work with the project team, team leaders, project delivery leads, and client stakeholders to create stand-out AI Security and Governance offerings powered by LLM platforms, frontier grade models, agentic frameworks, and AI/MCP gateways (Anthropic Claude, OpenAI, Azure OpenAI as representative examples.

Secure AI Engineer Manager

The Work: Applied Research & Innovation: Investigate active innovation frontiers in agentic AI systems - for example, agent memory and knowledge persistence architectures, model selection and inference routing strategies, autonomy and goal-anchoring control planes, and long-horizon task reliability. Translational Engineering: Translate research findings into production-grade implementations: engineered Python services, Node.js/TypeScript SDK modules, or platform-integrated components that other engineers and agent workloads depend on.

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