VP - AI & Digital Transformation

Company: Vashi Integrated Solutions Ltd.

Level: Vice President

Reports to: CEO

Location: Navi Mumbai

About Vashi: Vashi Integrated Solutions is an industrial B2B sourcing and distribution company for electrical and industrial products. Established in 1978, we serve customers across 100+ cities with 40+ product categories.

About the role: Vashi runs on capable technology platforms and a team that keeps them reliable. The next phase of growth depends on making Vashi faster and easier to do business with, taking time, cost and friction out of how the business runs, and making AI part of everyday work. This role is the single accountable owner for that change agenda. You will decide which workflows to transform and how, build the business case, take AI out of pilots and into daily use, and prove the result in turnaround time, customer experience and gross profit.

Key responsibilities:

Transformation portfolio and value:

- Own a prioritised map of end-to-end workflows, with a baseline and a hard target for cycle-time and cost reduction in each.

- Own the business case and benefits tracking for every transformation and AI initiative, validated by Finance.

- Drive build-vs-buy-vs-partner decisions with frugality.

AI capability:

- Set up the AI operating model: use-case pipeline, data readiness, guardrails, responsible use, adoption and measurement.

- Move AI from pilots to production across sales, procurement, credit, support and finance.

- Be the in-house authority on what AI can and cannot do for the business.

Data science and decision intelligence:

- Own the data science agenda for high-value workflows such as demand forecasting, replenishment, quote and margin optimisation, credit-risk scoring and procurement analytics.

- Build a lean data science and ML capability and run models as products, with clear ownership, measured value and monitoring.

- Set model governance covering validation, explainability, drift, bias and data-privacy compliance.

Customer experience and speed to market:

- Redesign customer-facing journeys from quote to order, order status, credit, delivery and service.

- Deliver faster quotation, lower turnaround time and fewer manual handoffs.

Leadership and governance:

- Set the transformation and AI direction and agree one shared roadmap with the Heads of Infrastructure, Platforms and Applications.

- Build a lean, senior core team across product, AI, automation and analytics, plus a network of digital champions in the business.

- Hold vendors and partners to outcomes.

- Present technology priorities to the board in commercial terms.

What success looks like in the first 12 months:

- A costed transformation and AI roadmap agreed with the CEO within 90 days, with a baseline and target for every priority workflow.

- At least two core workflows measurably faster and cheaper, with the change adopted.

- AI in live production use in more than one function, with measured impact.

- At least one data science model in live use and changing a real business decision.

- At least one customer-facing journey visibly faster or simpler.

- AI guardrails and responsible-use rules approved and operating.

Candidate profile:

Experience: 15+ years, including at least 5 years leading AI, data science or digital transformation with measured business outcomes.

Industry: a customer-facing, product-based, service-led business such as B2B distribution, industrial and engineering products, automotive and aftermarket, or retail and e-commerce. Pure-software, IT-services and back-office IT backgrounds are not a fit on their own.

Organisation size: has worked in an organisation with 6,000 - 8,000 Cr+ annual turnover and 3,000+ people across multiple locations.

Team managed: has led a multi-disciplinary team of roughly 20 - 25 people across data science, engineering, product and analytics. The core team at Vashi will start lean.

Budget: has directly owned an annual technology, digital or AI budget, with accountability for return, vendor negotiation and build-vs-buy decisions.

What we look for:

- A track record of workflow, cycle-time and customer-experience transformation, with time taken out and money saved.

- AI and data science models shipped into production, with real users and measured adoption.

- Commercial fluency in gross profit, working capital, cost-to-serve and ROI.

- A frugal approach, with value proven by a lean team before scaling.

- The ability to get change adopted through peers and business heads without direct authority.

- High ownership and trustworthiness: does what they say and surfaces bad news early.