Product Manager - Industrial

Job Title- Product Manager — Industrial

Location: Pune

Qualifications: 5+ Years

Horizontal Portfolio | Senior Individual Contributor

B2B Distribution Field Service AI Native Domain-Agile 0→1 & 1→N

Mandatory Skills: Product Management/Ownership, B2B SaaS & Industrial/Distribution/Field Service/Logistics domain experience, AI-native product experience, strong product strategy & 0→1/1→N delivery.

About Sonata Software

Sonata Software is an AI-first modernization engineering company that helps enterprises transform legacy systems into intelligent, scalable business platforms. Powered by its Platformation™ framework and Harmoni.AI platform, Sonata delivers AI-led modernization across cloud, data, AI, Dynamics, test automation, and managed services. Headquartered in Bengaluru, India, Sonata has more than $1.2 billion in revenue and 6,400+ AI engineers supporting global delivery across regions including the US, UK, India, Malaysia, Mexico, Australia, DACH, and the Nordics. With deep partnerships across Microsoft, AWS, Salesforce, and Snowflake, Sonata helps Fortune 500 enterprises accelerate innovation, improve efficiency, and drive sustainable growth. For more information, please visit www.sonata-software.com

About The Role

The Industrial vertical is our most complex and most valuable portfolio. It spans B2B e-commerce for distributors, CRM and sales analytics for industrial sales teams, field service management for equipment and mechanical service providers, logistics and dispatch software, pricing optimisation engines, and HVAC/mechanical workflow platforms. Every product in this portfolio serves operators, technicians, and sales reps working in environments where software failure has real operational consequences — not just a support ticket.

We are hiring a PM who has lived in at least one of these worlds — and can ramp intelligently into the others. Industrial distribution, field service, B2B commerce, and logistics each have their own vocabulary, their own data models, and their own deeply entrenched workflow patterns. We are not looking for someone to learn the industry from scratch. We are looking for someone who has already built product in adjacent operational complexity and knows how to transfer that pattern recognition.

Critically: this role requires an AI-native working style. Not AI awareness. Not AI features on a roadmap. We want a PM who already uses Gen AI as infrastructure for how they think, research, write, and decide — and who can identify and drive AI integration into the Industrial product portfolio with commercial and operational judgment.

The Industrial Portfolio — What You Will Own

This is the full scope. You will not own all of these equally from Day 1, but you need to understand all of them.

Product Area Platform(s) What It Does

B2B E-Commerce Channel Software, Aldrich Web Solutions Self-serve ordering, catalogue management, pricing, and account portals for industrial distributors and manufacturers. Multi-branch, multi-buyer complexity.

Industrial CRM & Sales Intelligence WebPresented, Rubber Tree Systems CRM, pipeline management, and sales analytics purpose-built for distribution sales teams — not generic Salesforce. Deep integration with ERP order data.

Field Service Management FieldConnect End-to-end job lifecycle for field technicians: dispatch, work orders, mobile execution, parts, invoicing, and customer sign-off. Offline-first requirements.

Logistics & Fleet Dispatch DQ Technologies Route optimisation, dispatch management, and fleet tracking for distributors running their own delivery operations.

Pricing Optimisation epaCUBE AI-assisted pricing intelligence and margin management for industrial distributors — matrix pricing, contract pricing, competitive benchmarking.

HVAC & Mechanical Workflow BuildCentrix Job management, estimating, service agreements, and compliance workflows for HVAC, mechanical, and building services contractors.

DOMAIN EXPERIENCE — WHAT WE ARE LOOKING FOR (AND WHAT WE ARE NOT)

This Is The Section Most Candidates Misread. We Are Not Requiring Direct Industrial Software Experience. We Are Requiring Operational Domain Depth In At Least One Of The Following Areas — And Demonstrated Ability To Ramp Intelligently Across Adjacent Domains. Here Is Exactly What Signals Tell Us You Can Do This Job

Domain / Signal What Good Looks Like Red Flag

B2B Distribution / Supply Chain Has built product for distributors, wholesalers, or manufacturer reps. Understands ERP integration complexity (SAP, NetSuite, Epicor). Has navigated multi-buyer, multi-branch account hierarchies. Only knows B2C commerce. Has never dealt with contract pricing, customer-specific catalogues, or EDI integration.

Field Service / Technician Workflows Has shipped a mobile-first product used by field workers. Understands offline-first design, parts/inventory lookup on-device, job lifecycle from dispatch to invoice. Has talked to technicians, not just managers. Field service only as an admin dashboard feature. Never designed for low-connectivity or non-desk users.

Industrial CRM / Sales Intelligence Has built CRM or sales analytics for a complex B2B sales motion — long cycles, multiple stakeholders, ERP-integrated pipeline data. Understands gross margin by product line as a selling metric. Generic CRM experience (Salesforce, HubSpot) without industrial or distribution domain depth.

Logistics / Dispatch / Fleet Has shipped route optimisation, dispatch management, or fleet tracking product. Understands driver workflow and last-mile delivery operations from the operator's perspective. Logistics only as a backend API or data pipeline project — no operator-facing product experience.

Pricing / Revenue Intelligence Has owned pricing strategy or pricing tooling product — tiered pricing, contract pricing, margin analysis. Understands that pricing in B2B is a product capability, not a spreadsheet. Pricing as a checkout feature. No understanding of distributor margin dynamics or competitive price positioning.

The Domain Ramp Test — We Will Assess This Directly

 We will give you a domain you do not know and watch how you learn it. Strong candidates use Gen AI to build context fast (competitor research, user review synthesis, regulatory landscape), then validate with users, then form a point of view. They do not wait to be taught.

 In the interview, you will be asked: 'You have joined as PM for FieldConnect (field service management). You know nothing about this space. Walk me through what you do in your first 30 days.' There is no right answer — only revealing ones.

 Candidates who have worked in a single domain for 5+ years without demonstrated cross-domain ramp are a risk. We weight recent ramp evidence (last 2–3 years) more heavily than historical depth.

Key Responsibilities

Product Strategy & Roadmap

 Own the product roadmap across the Industrial portfolio — not as a backlog manager but as a strategic owner who can say no, sequence for compounding impact, and connect features to revenue and retention outcomes.

 Define product positioning for each platform relative to incumbents — understand where we win, where we are vulnerable, and what needs to change to shift those dynamics.

 Partner with the Functional Architect to ensure new capabilities are built on a coherent domain model, not as isolated feature additions.

 Run structured discovery: user interviews with distributors, field technicians, fleet operators, and sales teams. Synthesise findings into product decisions, not just requirements documents.

 Own the 0→1 product bet when new capabilities are needed — define scope, validate early, ship iteratively. Delivery & Stakeholder Ownership

 Work closely with engineering leads to translate strategy into well-scoped epics and sprint-ready stories — raise the quality of requirements so engineering can move fast without constant clarification.

 Own product metrics across the Industrial portfolio: feature adoption, workflow completion rates, time-in-workflow, NPS by user type, and retention.

 Engage directly with enterprise clients — distributors, field service operators, fleet managers — to validate product direction, close feedback loops, and build relationships that improve renewal rates.

 Maintain competitive intelligence across direct competitors in each product area: GorillaDesk, ServiceTitan, Jobber (field service); NetSol, Prospect (B2B e-commerce); Vendavo, Zilliant (pricing).

 Present roadmap direction to internal stakeholders and external customers with clarity and conviction — including when the answer is 'we are not building that.'

Ai-native — What This Means For This Role Specifically

We use 'AI-native' deliberately. It is not a checkbox on the job description. Here is what it means in practice for an Industrial PM:

AI in Your Daily PM Work

 You use Claude, ChatGPT, or Perplexity as a standard research tool — for competitor analysis, user review synthesis, regulatory landscape mapping, and domain ramp on new verticals.

 You draft PRDs, discovery briefs, and competitive summaries with AI as a first-pass tool and apply your own judgment to refine them — not the other way around.

 You use AI to identify patterns across user feedback at scale, not just to summarise individual interviews.

 You can show us a specific example of how AI changed a product decision you made in the last six months — not just made you faster. AI in the Industrial Products

 Pricing intelligence: AI-powered margin optimisation and competitive price positioning for distributor sales teams (epaCUBE). You understand what data is needed, what the privacy and transparency requirements are, and where AI adds confidence vs. where it introduces risk.

 Intelligent dispatch: AI-assisted technician scheduling using location, skill, job history, and part availability (FieldConnect). You can define the functional model, not just the feature description.

 Sales signal detection: next-best-action recommendations for industrial CRM based on order patterns, product usage, and churn signals (WebPresented).

 Demand forecasting: AI-powered order prediction and inventory replenishment for distributors (Channel Software).

What 'AI-native' Is NOT In This Context

 Listing 'AI' in your skills section without being able to demonstrate a specific workflow change.

 Having shipped an AI feature (e.g. a chatbot) without being able to explain the data requirements, model constraints, and fallback design.

 Using AI only for writing assistance. That is table stakes, not AI-native.

 Describing AI strategy in terms of 'we should explore ML for X' — we want PMs who can define what good looks like and drive it to delivery.

Qualifications

Must-Have Requirements

 Minimum 5 years of product management or product ownership experience, with at least 2 years in a B2B SaaS product where your users were operational staff — not knowledge workers at a desk. Field technicians, warehouse operators, route drivers, or distribution sales reps count. Generic enterprise SaaS users do not.

 Demonstrated domain depth in at least one of: industrial/commercial distribution, field service management, B2B e-commerce for manufacturers, fleet/logistics operations, or pricing intelligence for B2B. You should be able to talk fluently about the business model, the data model, and the competitive landscape in your domain without preparation.

 Proven domain ramp across more than one product area — you have moved between product domains and have a clear method for building context quickly. You can describe exactly how you did it.

 Active Gen AI usage in your PM workflow — not aspirationally. Specific tools, specific use cases, specific judgment calls you have made because of AI-surfaced insight.

 Track record of shipping product that changed a measurable operational outcome for your users — not just features that shipped on time.

Strongly Preferred

 Prior exposure to ERP integration in a B2B context — SAP, NetSuite, Epicor, Prophet 21. You do not need to have built the integration, but you need to understand why ERP is the source of truth and what that means for product design.

 Experience with mobile-first product design for field or warehouse contexts — offline sync, low-connectivity UX, device constraints.

 Understanding of multi-sided B2B pricing: contract pricing, tiered pricing, customer-specific catalogues, gross margin dynamics.

 MBA or equivalent structured thinking program — relevant because Industrial PM requires both operational empathy and strategic framing simultaneously.

 Experience working with or selling to distributors, contractors, or field service operators — not just building for them from behind a screen. Tools & Platforms

 Product: Jira, Productboard, Linear, Confluence

 Design: Figma, Miro, FigJam

 Gen AI: Claude, ChatGPT, Perplexity, Cursor, Lovable, Notion AI

 Analytics: Mixpanel, Amplitude, Metabase, SQL (working proficiency)

 Competitive intelligence: G2, Capterra, TrustRadius — and knowing how to read between the lines of user reviews

 Domain reference tools: Trade publications (Industrial Distribution, Field Service News, Modern Distribution Management)

What Makes This Role Hard — And Why That Matters

The Honest Brief on This Portfolio

 Multi-sided operational complexity: your users are distributors AND their customers AND their field technicians AND their fleet drivers — sometimes in the same product. Priorities conflict constantly.

 Legacy system reality: most clients run ERP systems that are 10–20 years old. Your roadmap must account for integration constraints that are not negotiable and that no amount of product vision can override.

 Long B2B sales cycles mean product decisions affect win rates 6–12 months later, not next sprint. You need to think about pipeline impact as well as retention impact.

 Operational users have low tolerance for software that slows them down. A field technician using FieldConnect mid-job cannot afford a 3-second load time or a confusing 4-step workflow. Your definition of done must reflect this.

 The AI opportunity is real but the data quality is inconsistent. Pricing intelligence and demand forecasting are valuable — but only if the underlying distributor data is clean. You will need to design for data quality as a product problem, not an engineering precondition.

AI OPPORTUNITY IN THE INDUSTRIAL PORTFOLIO

This is one of the most underserved verticals for AI in enterprise software. The opportunity is significant, the data exists, and the ROI is legible. The PM who owns this portfolio will be expected to have a point of view on where AI creates compounding value — and where it creates noise.

Near-Term AI Opportunities

 Intelligent pricing recommendations for distributor sales reps — margin optimisation by customer, product line, and competitive context (epaCUBE).

 AI-assisted technician dispatch using skill match, location, job history, and parts availability — reducing first-visit failure rates (FieldConnect).

 Sales signal detection and next-best-action in industrial CRM — identifying at-risk accounts and cross-sell moments from order pattern data (WebPresented).

 Automated work order generation from service history and asset data — reducing technician admin time before and after jobs (BuildCentrix). Medium-Term AI Opportunities

 Demand forecasting for distributor inventory replenishment — integrating order history, seasonality, and supplier lead times (Channel Software).

 Route and load optimisation for fleet dispatch — dynamic re-routing based on real-time delivery status and traffic data (DQ Technologies).

 Natural language search across industrial product catalogues — enabling non-expert buyers to find the right part without knowing the SKU (Channel Software, Aldrich).

 Predictive maintenance flagging within service agreements — surfacing early failure indicators from job history and asset data (BuildCentrix, FieldConnect).

What We Offer

Why This Role Is Different

 Ownership of a portfolio that directly affects how distributors, field technicians, and fleet operators work every day — these are not abstract software users.

 The most significant AI opportunity in our entire product portfolio — and the expectation that you will drive it with commercial judgment, not just engineering enthusiasm.

 Direct access to enterprise clients from Day 1 — you will talk to distributors and operators, not proxy through customer success.

 A Functional Architect and Product Owner working alongside you — so you can focus on the strategy and discovery work, not get pulled into sprint ceremonies.

 Competitive compensation with a performance-linked trajectory tied to vertical revenue and product adoption metrics.

This is a portfolio built on operational complexity. If that is where you have done your best work — apply.