Head of AI Solutions & Delivery – Metals Division

Location: Pune

Experience: 10 Years

Employment Type: Full-Time

Reporting To: CEO

Division: Industrial AI – Metals Manufacturing

Role Overview

We are looking for an experienced technology and business leader to head the Metals Division, drive strategic growth, lead customer engagements and deliver high-impact Industrial AI solutions across the metals manufacturing ecosystem.

This is a strategic yet hands-on leadership role requiring a strong understanding of manufacturing operations, AI/ML modelling and software solution delivery.

The individual will lead multidisciplinary teams comprising Data Scientists, ML Engineers, Software Engineers and Metallurgy/Process Experts while working closely with customers to identify manufacturing challenges, design AI-led solutions and translate them into measurable business outcomes.

The role requires someone who can confidently operate across three critical areas:

- Business Leadership: Build the division, drive revenue, develop customer relationships and expand business.
- Technical Leadership: Guide AI/ML modelling, industrial software architecture and solution productization.
- Delivery Leadership: Own end-to-end project execution, customer satisfaction and measurable business impact.

Key Responsibilities
- Division Leadership & Business Growth

- Lead the Metals Division end to end, owning strategy, revenue growth, customer portfolio, delivery targets and business planning.
- Build, mentor and lead multidisciplinary teams across Data Science, Machine Learning, Software Engineering and Metallurgy.
- Establish team objectives, hiring strategies, technical standards and performance expectations.
- Define the division's solution and product roadmap in collaboration with product and business teams.
- Identify scalable and repeatable AI use cases across steel, aluminium and other metals manufacturing processes.
- Drive business development through solution design, technical proposals, RFP/RFI responses, proof-of-concept planning and commercial discussions.
- Expand existing customer relationships while identifying and converting recent business opportunities.

2. Customer Engagement & Solution Consulting
- Serve as the senior technical and executive point of contact for metals manufacturing customers.
- Build trusted relationships with Plant Heads, Process Engineers, Quality Leaders, IT/OT Teams and senior management.




- Lead customer discovery sessions, technical workshops and shop-floor discussions to understand manufacturing processes and operational challenges.
- Translate business requirements into AI use cases, solution concepts, high-level architectures and implementation roadmaps.
- Define project scope, technical feasibility, success criteria and measurable business outcomes.
- Conduct technical presentations, solution demonstrations and customer workshops.
- Communicate technical capabilities, project methodology, differentiation and expected business value to technical as well as executive stakeholders.

3. Project & Delivery Excellence
- Own end-to-end delivery of Metals Division projects, from initial scoping and data onboarding to AI model development, deployment and value realization.
- Ensure projects are delivered within agreed timelines, budgets, scope and quality standards.
- Establish delivery governance covering project plans, milestones, risks, dependencies, customer reporting and escalations.
- Evaluate technical feasibility before project commitments, considering data readiness, integration requirements and deployment constraints.
- Manage customer expectations while aligning project commitments with team capacity and technical readiness.
- Track measurable business improvements, including scrap reduction, production yield, first-pass quality, energy consumption per tonne and unplanned equipment downtime.
- Demonstrate realized customer value to drive renewals, account expansion and long-term partnerships.

4. Technical, Data Science & AI Leadership
- Provide technical direction on AI/ML approaches for industrial and metals manufacturing applications.
- Guide projects involving predictive quality, predictive maintenance, process optimization, anomaly detection and time-series modelling.
- Evaluate and guide the application of deep learning, optimization techniques and hybrid physics-informed models.
- Review solution architectures and engineering practices to ensure scalability, robustness and maintainability.




- Establish standards for software engineering, MLOps, model monitoring, testing and deployment.
- Identify reusable intellectual property, algorithms, models and software components across customer projects.
- Drive productization of successful project solutions into configurable, scalable offerings for the metals sector.
- Evaluate emerging technologies, including Generative AI, LLMs and industrial copilots, for practical manufacturing applications.

Required Qualifications & Experience
- Bachelor's or Master's degree in Engineering – Metallurgical, Mechanical, Electrical, Chemical, Computer Science or a related discipline.
- Postgraduate qualification in Data Science, AI or Computer Science will be an added advantage.
- 10 years of professional experience in Industrial AI, Manufacturing Technology, Industrial Software or technology-led solution delivery.
- Demonstrated experience leading technical teams, customer engagements and complex technology projects.
- Mandatory manufacturing exposure: Direct experience working with manufacturing plants, shop-floor operations or manufacturing operations teams.
- Metals manufacturing exposure in steel, aluminum, copper, foundry, casting, rolling, forging, extrusion or heat treatment is strongly preferred.
- Candidates from automotive, heavy engineering or process manufacturing environments may also be considered.
- Proven experience leading software product or solution delivery teams.
- Strong understanding of SDLC, including requirements, design, development, testing, deployment and maintenance.
- Hands-on coding exposure in Python is mandatory, with working familiarity with SQL.
- Strong understanding of AI/ML modelling, including problem framing, feature engineering, model selection, validation and deployment.
- Hands-on involvement in AI/ML modelling projects, preferably involving industrial, sensor or time-series data.
- Proven customer-facing leadership, including requirements gathering, technical presentations and executive stakeholder management.
- Experience managing project timelines, delivery scope, quality, risks and customer satisfaction.
- Exposure to solution architecture, presales, technical proposals and productization of technology solutions.
- Strong people leadership, communication, analytical and problem-solving capabilities.
- Willingness to travel to customer manufacturing plants as required.

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