EVA Professional

Basic Requirements

• Lead discovery workshops with business stakeholders to identify pain points, opportunities, and AI transformation use cases.

• Design and articulate end-to-end agentic solution for enterprise process/functional use-cases - the agent hierarchy, target-state agentic architecture, value streams, agent interation models and transformation roadmaps. (with technical depth and agentic system build experience in 1 platform or functional area - GCP, AWS, Snowflake, DataBricks, Azure, Anthropic)

• Assess enterprise data maturity, governance and technology readiness to shape scalable AI adoption.

• Lead solution definition across business, architecture, data, and engineering teams while ensuring end-to-end traceability from business value to implementation.

• Develop value framework for Agentic AI with the right industry/clinet context. Using the framework, build executive business cases including value estimation, investment requirements, KPIs, and benefits realization.

• Drive business readiness and change management by defining stakeholder engagement, communication, training, and adoption plans for AI transformation initiatives.

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Good to Have

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• Experience defining enterprise data strategies, data products, and AI-ready data foundations.
• Exposure to knowledge architecture, semantic layers, and enterprise knowledge management.
• Experience designing AI governance frameworks, operating models, and organizational readiness for AI adoption.
• Strong consulting, executive communication, stakeholder management, and problem-structuring skills with experience leading cross-functional delivery teams.

Tech fluency

• Deep in at least one platform (AWS, Azure, Google Cloud), data platforms (Databricks, Snowflake), or foundation models (e.g., Anthropic, OpenAI). and broadly credible across all three categories. Can shape platform and model choices with a clients tech leadership.
• Fluent enough in the agentic AI stack to judge where autonomous systems create real value versus hype, and to shape platform and model choices with a clients tech leadership.

Industry Lens:

• Recognized depth in at least one priority industry (Consumer Goods, Retail, Life Sciences, Banking); knows its core processes well enough to challenge how they are run today and engage that C-suite credibly.

Role Summary

• • Min. 10 yrs overall, incl. AI data projects
• • High-value consulting; large-scale delivery with minimal oversight
• • Has led at least one end-to-end process reengineering or reinvention engagement
• • Process modelling and requirements definition at enterprise scale
• • Manages senior stakeholders
• • Awareness of AI governance and regulation (e.g., EU AI Act, model risk)
• • Structured problem-solving; program management; strong communication

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