Required Qualifications

Education

Bachelor's or Master's degree in Engineering, Computer Science, Industrial Engineering, Data Science, or related field.

Experience

7+ years of experience in Manufacturing, Industrial Operations, Digital Manufacturing, Industry 4.0, or Industrial Digital Transformation.

3+ years designing and deploying AI, Analytics, Machine Learning, or GenAI solutions.

Experience leading large-scale enterprise transformation programs.

Robust client-facing consulting and solution architecture experience.

Required Technical Skills

AI & Advanced Analytics

Generative AI and Large Language Models (OpenAI, Azure OpenAI, Anthropic, Gemini, etc.)

Agentic AI and Multi-Agent Architectures

Machine Learning and Predictive Analytics

Computer Vision

Time-Series Analytics

Knowledge Graphs (Neo4j preferred)

RAG Architecture and Vector Databases

Cloud & Data Platforms

Microsoft Azure AI Services

Azure Data Platform

Databricks

Microsoft Fabric

AWS or Google Cloud AI Platforms

Data Engineering and Data Governance

Industrial & Manufacturing Systems

MES (AVEVA, Siemens Opcenter, Rockwell, Dassault, SAP ME)

SCADA, DCS, PLC Ecosystems

Historians (PI, IP21, Canary)

ERP (SAP, Oracle)

PLM and Engineering Systems

IIoT Platforms

Architecture & Engineering

Enterprise Architecture

Solution Architecture

API and Integration Design

MLOps / LLMOps

AI Governance & Responsible AI

Cybersecurity for Industrial Environments





Preferred Qualifications

Experience in Manufacturing Copilots, Operations Copilots, or Engineering Assistants.

Experience with Digital Twin platforms and simulation technologies.

Certifications in Azure AI, Azure Solutions Architecture, AWS ML, or equivalent.

Experience working with industrial data platforms such as Cognite, AVEVA CONNECT, or DataHub platforms.

Familiarity with autonomous operations and closed-loop optimization systems.

Key Competencies

Strategic Thinking

Executive Communication

Consultative Problem Solving

Innovation Mindset

Cross-Functional Leadership

Architecture Governance

Manufacturing Domain Expertise

Stakeholder Management

Business Value Realization

Success Metrics

AI solutions successfully deployed into production.

Measurable client outcomes such as productivity improvement, cost reduction, quality enhancement, and operational efficiency gains.

Growth of AI-driven business pipeline and revenue.

Development of reusable assets and industrial AI accelerators.

Increased adoption of AI across manufacturing and industrial operations.

Client satisfaction and executive stakeholder trust.

Ideal Profile A visionary technology leader who understands both the factory floor and the AI frontier—capable of transforming industrial operations through scalable, responsible, and outcome-driven AI solutions.

📌 AI Architect - Pan India (Pune)
🏢 Capgemini
📍 Pune