- End-to-end program ownership. Define scope, milestones, and success metrics for platform initiatives. Translate business needs into an execution plan engineers can build against — not a wishlist.
- The platform–channel contract. Keep platform capability and channel adoption aligned. When their priorities pull in different directions, you make the trade-off call and defend it with data.
- Technical dependencies and risk. Read the system well enough to see roadblocks before they land — API limits, data gaps, sequencing conflicts — and resolve them without waiting for someone to escalate.
- Adoption, not just delivery. A capability nobody uses didn't ship. Drive change management with internal clients so teams actually get value from what we build.
- The number. Instrument what you own. Track program performance on real metrics, run the analysis yourself, and iterate on what the data says — not on vibes.
- You operate with AI as a force multiplier. LLM tools, agents, and automation are part of how you draft specs, query data, prototype, and compress the boring parts of the job. You show up faster because of it, and you can point to what you've built or automated.
- You can hold a technical AI conversation. You reason credibly about APIs, retrieval, evals, tokens, and latency-versus-cost trade-offs. You don't need to train a model, but you won't get bluffed by an ML or engineering team, and you can spec an AI-touching feature without hand-waving.
- Technically fluent, business-first. You read PRs and SQL, follow a system diagram, and challenge engineering on trade-offs — but your job is outcomes, and you drive tech through influence and judgment, not by grabbing the keyboard.
- Full owner. You take an account or a program and run it with minimal oversight. Nobody has to chase you for status; you're already three steps ahead.
- Fast on new domains. You get to functional understanding of an unfamiliar system quickly, then keep the business need and the platform capability honest with each other.
- Multi-stakeholder operator. You balance platform and channel priorities, work across engineering, product, and business, and keep everyone moving without turning into a message-relay.
- Calm in ambiguity. Evolving requirements don't rattle you — you bring structure and a clear next step where there wasn't one.
- 5–7 years in technical program management, product management, or product ownership at a product-first or platform-driven company. We weight trajectory, AI fluency, and ownership over raw years — a sharp AI-native operator with 4 strong years beats a 7-year coordinator.
- Proven multi-team delivery across internal and external stakeholders.
- Strong analytical instinct — you use data to decide, and you can pull and read it yourself
- Experience in SaaS, platform ecosystems, or e-commerce technology.
- Working command of Agile / Lean / Kanban, and the tools that run them (JIRA, Asana, or equ
- Communication and leadership that lets you influence across functions without positional authority.
- Bachelor's in Business, Computer Science, or a related field. PMP / CSM a plus, not a gate
- You've shipped or owned an AI-touching product surface — recommendations, search, an agent talk about its failure modes.
- You've built your own internal tools or automations to make a team faster.
- CS background or a past life close to engineering.
- Flex University: Access in-house learning sessions and workshops designed to enhance your professional and personal growth.
- Learning Wallet: Enrol in external courses or certifications to upskill—we’ll reimburse the costs to support your development.
- Regular community engagement and team-building activities
- Biannual events to celebrate achievements, foster collaboration, and strengthen our workplace culture
Skills Required
- 5-7 years of experience in technical program management, product management, or product ownership at a product-first or platform-driven company
- Proven multi-team delivery across internal and external stakeholders
- Strong analytical ability, including independently pulling and interpreting data
- Experience in SaaS, platform ecosystems, or e-commerce technology
- Working command of Agile, Lean, or Kanban and tools such as JIRA or Asana
- Communication and leadership skills to influence across functions without positional authority
- Bachelor's degree in Business, Computer Science, or a related field
- AI fluency, including practical use of LLM tools, agents, or automation
- Experience shipping or owning an AI-enabled product surface
- Experience building internal tools or automations
- Computer science background or prior experience working closely with engineering
- PMP or CSM certification
What We Do
Fynd is India's largest omnichannel ecosystem and multi-platform tech company. Headquartered in Mumbai and founded by Farooq Adam, Harsh Shah, and Sreeraman MG in 2012. We have modernized retail strategies for more than 1000 brands & created a rich suite of tech products. Rooted in technology & innovation, we have products in applied machine learning, big data, gaming+crypto, image editing, and learning space. Our constant innovation and expertise in technology has been noticed worldwide. Fynd made it to Fast Company's list of Top 10 most innovative Asia-Pacific companies of 2022. We are a fast growing team of 1000+ fun, skilled and ambitious people. We explore the unexplored, innovate unafraid, and have the time of our life while we do. Be a part of the new. Join us. For more information about our products, visit us at www.omnifynd.com






