Palkin
Gupta
CSPO® Product Owner building AI-powered enterprise SaaS — from LLM + RAG systems, embeddings, and vector search to intelligent workflows and product releases Fortune 500 customers rely on.
GenAI & LLM Systems · RAG · Embeddings & Vector Search · AI Workflow Automation · Enterprise SaaS
5+
Years in product
8+
Enterprise releases
15+
Agile delivery cycles
GenAI
LLM + RAG systems
Open to roles
Product Owner · Product Manager · Business Analyst
The roles I'm actively exploring next, and the core strengths I bring to each one.
Summary
Product thinking, delivered end to end.
CSPO®-certified Product Owner with 5 years of experience across AI-powered enterprise SaaS, GenAI, and digital products. Skilled in product discovery, roadmap planning, backlog prioritization, and cross-functional delivery of systems that use LLMs, RAG, embeddings, vector search, re-ranking, and intelligent automation. Progressed into de facto product ownership for an enterprise AI search platform, delivering 8+ releases and partnering with Fortune 500 customers.
AI engine
Building with modern AI systems.
Product ownership across the stack that powers intelligent, retrieval-aware, and cost-effective AI applications.
LLM Models
Shaped requirements for LLM-powered features, model selection, and guardrails for safe completions.
RAG
Designed retrieval-augmented generation workflows that ground answers in enterprise content.
Embeddings
Specified embedding strategies for semantic search, recommendations, and clustering.
Vector Databases
Worked with engineering on vector DB selection, indexing, and schema design for retrieval at scale.
Re-ranking
Prioritized re-ranking and scoring logic to surface the most relevant results across noisy data.
Tokenization
Influenced token-budget design, context windows, and output constraints to keep AI features cost-effective.
Clustering
Applied clustering to organize content, users, and search signals into actionable product groupings.
APIs & Integrations
Translated REST APIs, model endpoints, and third-party services into user-facing capabilities and backlogs.
MCPs
Explored Model Context Protocols and tool-use patterns to connect agents with data and actions.
Cost Optimization
Drove cost-aware AI design: caching, chunking, model selection, and usage controls that protect margins.
Secure & Reliable AI
Defined safety, privacy, observability, and fallback requirements for reliable AI behavior.
Career highlights
Outcomes, not activity.
A snapshot of the measurable impact behind five years of product and business analysis work, including AI-powered enterprise systems.
GenAI
LLM + RAG systems delivered
Owned product requirements for AI-powered search, retrieval, and workflow automation that combine LLMs, embeddings, vector databases, and re-ranking.
30%
Fewer requirement gaps
Led discovery and user research with clients and stakeholders, translating ambiguous asks into clear, prioritized product specifications.
25%
Less requirement rework
Raised the bar on acceptance criteria and engineering handoffs across AI healthcare and Web3 product lines.
20%
Faster release velocity
Sharper backlog refinement, sprint planning and requirement clarity across 8+ enterprise releases of an AI search platform.
3x
Recognition for delivery
2x Star Performer of the Month and a Key Contributor Award for product delivery and cross-functional impact.
Rewards & recognition
Products
Platforms I've helped shape.
Select a product to see the problem space and what I owned.
Skills
Product management, grounded in business analysis.
Explore the toolkit by discipline.
Work experience
Where the work happened.
Expand a role to read the detail behind the impact.
- Owned product strategy, roadmaps, backlogs and feature prioritization across AI-powered Healthcare and Web3 products, aligning customer needs, business priorities, engineering capacity and product metrics.
- Led product discovery through user research with clients and stakeholders, translating ambiguous requirements into clear specifications and prioritized solutions — reducing requirement gaps by 30%.
- Strengthened requirement quality, acceptance criteria and engineering handoffs, contributing to a 25% reduction in requirement-related rework.
- Drove end-to-end delivery across discovery, requirements, design, development, UAT and release with Engineering, UI/UX, QA and Solution Architects.
- Defined compliance-oriented requirements and acceptance criteria for US healthcare workflows, supporting secure and audit-ready releases.
- Identified and prioritized GenAI and AI/ML opportunities — including LLM integrations, RAG, embeddings, vector search, re-ranking, agentic workflows, and intelligent automation — to reduce manual effort and improve user experience.
- Translated APIs, model endpoints, AI workflows, token budgets, and automation into user-centric requirements and actionable engineering backlogs.
- Used customer feedback, market analysis, business value, cost impact and technical feasibility to continuously refine the roadmap and improve delivery predictability.
- Progressed from Business Analyst to Senior Business Analyst / de facto Product Owner, taking ownership of product strategy, roadmap execution, backlog prioritization, requirements and feature delivery for an enterprise AI search platform.
- Owned the product backlog across 15+ Agile delivery cycles, converting enterprise customer needs into prioritized epics, user stories, acceptance criteria and release requirements for AI search, retrieval, and knowledge-management capabilities.
- Delivered 8+ enterprise releases, contributing to a 20% improvement in release velocity through better backlog refinement, sprint planning and clearer requirements.
- Partnered with AI/ML and Engineering teams on vector search, embeddings, content indexing, re-ranking, and search-relevance features that power Fortune 500 knowledge retrieval.
- Conducted discovery workshops, stakeholder interviews, user research, product demos and requirement validation with Fortune 500 customers.
- Prioritized 30+ product enhancements using data analysis of customer impact, business value, product strategy, technical feasibility and delivery dependencies.
- Collaborated with Product, Engineering, UX, QA and technical teams across APIs, workflows, customer journeys, UAT and release planning.
- Translated complex search, knowledge-retrieval, relevance, and retrieval-augmented generation requirements into customer-focused product capabilities.
- Authored BRDs, FRDs, PRDs, user stories, acceptance criteria and functional specifications, improving requirement quality and reducing downstream rework.
- Mentored junior Business Analysts on Agile delivery, user story writing, requirements analysis and backlog management.
CSPO® certification
Certified Scrum Product Owner®
An industry-recognized credential that sharpens how I translate strategy into shipped product value.
Certified Scrum
Product Owner
Issuing Body
Scrum Alliance
Issued Date
10 Dec 2025
Valid Through
10 Dec 2027
CSPO training validates the ability to manage product backlogs, prioritize by value, and align stakeholders around customer outcomes — the same skills behind every roadmap and release I ship.
Credential ID
2125990
Certifications & education
Credentials that back the craft.
- CSPO®: Certified Scrum Product OwnerScrum Alliance
- Mastering Claude Cowork & AI AgentsCourse
- HIPAA Compliance EssentialsGreat Learning
- Google Analytics CertificationGoogle
- Business Analysis ProcessCourse
2025 — 2027
MBA, Business Analytics
Symbiosis School for Online and Digital Learning
Pune, India · In progress
2017 — 2021
B.Tech, Computer Science Engineering
Shoolini University
Solan, India · GPA 7.6
Contact
Let's talk about your AI product roadmap.
Open to Product Owner and Product Manager roles on GenAI, LLM + RAG, and enterprise AI SaaS products. Happy to walk through discovery, delivery, and AI-system outcomes in detail.
palkingupta7@gmail.comPalkin Gupta · CSPO® Product Owner · 2026