Sigma Allied Services - Senior Manager - Enterprise AI Value Strategy

Job location: [{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Hyderabad","addressCountry":"IN"}},{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Bangalore","addressCountry":"IN"}},{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Pune","addressCountry":"IN"}}] Work arrangement: Employment type: FULL_TIME Salary: "" Experience requirements: {"monthsOfExperience":168,"educational":{"credentialCategory":"bachelor degree"}} Education requirements: "" Role & responsibilities: L3 (Must Have): - Enterprise AI Strategy, Agentic AI Solutioning, AI Platform Strategy, Agentic Hierarchy and Design, and AI and Data Architecture (with technical depth and agentic system build experience in 1 platform or functional area - GCP, AWS, Snowflake, DataBricks, Azure, Anthropic). - CxO Advisory, Enterprise Transformation, Business Function Transformation, and AI Transformation Roadmaps. - Enterprise Data Strategy, Data Products, Semantic Layer, and BI Strategy. - AI Business Case, Value Realization, AI & Data Roadmap, and AI Maturity Assessments. - GTM & Origination. L2 (Good to have): - L3 Skills + Operating Model & Org Redesign. L1 (Ideal Candidate): - Both L3 & L2 Skills + AI Governance, AI Risk & Compliance, Large Deal Shaping, and Alliance & Ecosystem Management. Preferred candidate profile: Basic Requirements: - Shape enterprise AI strategy and advise C-suite stakeholders on AI-led business, technology, and functional transformation. - Lead executive discovery sessions to identify enterprise AI opportunities and define AI transformation roadmaps, investment priorities, and value realization strategies. - Define enterprise AI and data architecture, including AI platform strategy, agentic architectures, enterprise data strategy, data products, semantic layer, and target-state AI capabilities (with technical depth and agentic system build experience in 1 platform or functional area - GCP, AWS, Snowflake, DataBricks, Azure, Anthropic). - Develop executive business cases, AI maturity assessments, value frameworks, and AI & data roadmaps to accelerate enterprise AI adoption. - Lead multidisciplinary consulting teams across strategy, architecture, data, engineering, and change management while owning executive relationships and client outcomes. - Drive practice growth through GTM development, solution innovation, proposal leadership, and AI opportunity origination.