Enterprise AI Value Strategy -Supply chain+Data science +Enterprise AI (Bengaluru)

Enterprise AI Value Strategy -Supply chain+Data science +Enterprise AI (Bengaluru)

24 Oct
|
Sigma Allied Services
|
Bengaluru

24 Oct

Sigma Allied Services

Bengaluru

Role & responsibilities

Sr. Manager :8+ yrs

Consultant 5+ yrs

Mandatory skills: Enterprise AI + Supply Chain + Data Science

Bangalore/Pune/Mumbai/Noida/Hyderabad

Agentic AI Solutioning & AI Strategy Blueprint

- Design and develop AI Strategy Blueprints by synthesizing business objectives, current-state assessments, and AI opportunity landscapes into prioritized, actionable enterprise AI roadmaps.
- Architect Agentic AI solutions defining agentic hierarchies, agent roles, and orchestration patterns with hands-on experience in at least one platform (GCP, AWS, Azure, Databricks, or Snowflake).
- Design and document agentic workflows that connect AI agents to enterprise data systems, APIs, and business processes to automate and augment decision-making at scale.

Business Process, Functional Specifications & Business Case Development
- Own or lead the development of Business Requirements Documents (BRDs) and Functional Specifications that translate business needs into structured, technically deliverable AI and data initiatives.
- Map and analyze current-state business processes to identify AI intervention points; define future-state workflows that incorporate agentic and AI-enabled capabilities.
- Build structured AI business cases with quantified value levers — including ROI, cost-benefit analysis, and payback timelines — to support client decision-making and investment prioritization.

Data Management, Analytics & Data Foundation
- Apply foundational Data Management principles — including data governance, data quality, and master data management — to assess and strengthen client data foundations for AI readiness.
- Conduct data analysis to surface insights from client datasets that validate AI prospect sizing, support business case development, and inform strategy recommendations.

Data Products & Enterprise Data Modeling




- Support the design of Enterprise Data Models that structure client data assets for AI and analytics consumption, ensuring consistency, reusability, and scalability across functions.
- Contribute to the definition and development of Data Products — curated, governed data assets — that serve as reliable inputs to AI models, agents, and reporting pipelines.

Knowledge Layer, Prompt Engineering, RAG & AI Platform Advisory
- Apply Knowledge Graph and Knowledge Layer concepts to structure enterprise information for AI consumption, enabling more accurate and context-aware agentic reasoning.
- Design and apply Prompt Engineering techniques and Retrieval-Augmented Generation (RAG) frameworks to enhance AI solution performance and ground model outputs in client-specific knowledge.
- Develop AI Capability Roadmaps that sequence the build-out of AI skills, platforms, and talent across the enterprise; conduct AI Platform Assessments to evaluate technology fit and readiness.

EDUCATION
- Bachelor’s degree required; MBA or master’s in business analytics , Supply Chain, Data Science, Computer Science, Industrial Engineering, Applied Math/Statistics, Operations Research, or a related discipline preferred.

BASIC (REQUIRED) QUALIFICATIONS
- 5–6 years of experience in management consulting, AI strategy, data strategy, or enterprise technology advisory — with demonstrated client or stakeholder-facing responsibilities.
- Demonstrated ability to design Agentic AI solutions or AI Strategy Blueprints, including hands-on experience defining agentic hierarchies or AI platform architecture within at least one enterprise platform (GCP, AWS,



Azure, Databricks, or Snowflake).
- Hands-on experience developing BRDs, Functional Specifications, or process maps in the context of AI or data-driven transformation programs.
- Experience building AI or digital transformation business cases, including value quantification, ROI modeling, and executive-level presentation.
- Foundational knowledge of Data Management, Data Analytics, and Data Foundation concepts relate to enabling AI systems and enterprise AI adoption.
- Strong exposure to Agentic AI frameworks, LLMs, Vector DB, Prompting techniques & RAG Architecture.
- Strong written and verbal communication skills with demonstrated ability to convey complex AI and data concepts clearly to non-technical business audiences.

PREFERRED QUALIFICATIONS
- Hands-on experience with Knowledge Graph design, Prompt Engineering, or RAG applied to enterprise AI solutions
- Familiarity with Enterprise Data Modeling or Data Products; certifications or hands-on proficiency in one or more platforms: GCP, AWS, Azure, Databricks, Snowflake, or Anthropic.
- Familiarity with enterprise planning or ERP platforms (e.g., SAP IBP, o9, Kinaxis, Blue Yonder, Anaplan, Oracle SCM)
- Exposure to industrial platforms (e.g. Cognite, C3.AI, Aspen MTELL, Aveva).
- Working knowledge of data visualization or analytics tools (e.g., Power BI, Tableau, Python, SQL)
- Exposure to optimization concepts (LP, MILP), commercial solvers (Gurobi, CPLEX), simulation algorithms (Monte Carlo simulation).
- Exposure to procurement tools like Ariba/Zycus/ Ivalua
- Exposure to decision intelligence tools like Aera technology & modules like Process Builder, Business Rules, Simulation & Planning, and Decision Boards
- Program management experience; participation in AI hackathons, strategy projects, or competitions with measurable outcomes.

Preferred candidate profile

📌 Enterprise AI Value Strategy -Supply chain+Data science +Enterprise AI (Bengaluru)
🏢 Sigma Allied Services
📍 Bengaluru

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