Product Manager

Mstack AI·Bengaluru·Onsite

APMLogisticsEnterpriseAI

Experience

1–3 years

Employment

Full Time

Work mode

Onsite

Level

APM

Location

Bengaluru

Posted

6 days ago

About the role

Mstack is a tech-enabled specialty chemicals company that runs global sourcing, sales, logistics and finance on its own platforms. The Product team builds and runs SalesStack, ProcureStack and LogiStack, and integrates them with our ERP (Microsoft Dynamics Business Central).

We are now moving manual, high-volume work - supplier and customer emails, follow-up calls, document generation, invoice posting - to AI agents and automated workflows. This role sits at the centre of that shift.

What you'll do

User research: spend time with sales, procurement, logistics and finance users; run interviews, shadow workflows and turn what you see into clear problem statements.
Problem definition: size the problem with data (time lost, cost, error rates, revenue at risk) and decide what is worth solving now.
Solutioning: explore options, weigh trade-offs, and pick the simplest solution that moves the metric - software, AI agent, automation or process change.
PRDs: write crisp PRDs with goals, non-goals, user flows, edge cases, success metrics and acceptance criteria that engineering can build from.
UI/UX: create wireframes and flows in Figma (or prototype directly with AI tools) and review designs for usability.
Delivery: work with engineering through sprints, unblock decisions, groom the backlog and own release quality.
GTM and adoption: plan rollout, train users, write release notes and track adoption until the feature is actually used.
Ownership: own one or more product areas end to end, with metrics you report on to leadership.
Spot AI opportunities: find repetitive, rules-heavy or communication-heavy work across teams and judge where AI is the right tool and where it isn't.
Design agentic workflows: define what an agent does, which tools and data it uses, where a human approves, and how it fails safely — for email, voice and document-based workflows.
Prototype fast: build working prototypes and internal tools yourself using tools like Claude Code, Cursor, Lovable, n8n or Zapier before asking engineering to build at scale.
Spec AI features well: write PRDs that cover prompts, context, evaluation sets, accuracy targets, guardrails, cost per run and human-in-the-loop design.