Product Owner

Doctutorials Edutech Pvt Ltd; Hyderabad; On-site; INR 1,200,000 - 1,800,000; Full time

Job summary

Doctutorials Edutech Pvt Ltd is seeking a Product Owner to translate product priorities into clear work items across medical-education and other business-priority products. You will own backlog, ensure value delivery, and guide release readiness through collaboration with Engineering, Design, QA, Academics, Operations and Support.

The role emphasizes defining AI use cases, data traceability, human validation, and safety. You will balance scope, risk, and impact in a fast-paced environment.

Qualifications

• Translate product goals into user journeys, epics and stories.
• Own and refine backlog based on value and risk.
• Collaborate daily with engineering, design, QA, academics, operations and support.
• Define AI use cases with data, traceability and safety expectations.

Responsibilities

• Translate product goals into user journeys, epics, and measurable acceptance criteria.
• Own and refine backlog; decide scope and priorities during execution.
• Work daily with cross-functional teams; participate in planning, reviews, UAT and release readiness.
• Define practical AI use cases and ensure data traceability, validation, and safety.

Skills

Backlog management

Requirement ownership

Cross-functional collaboration

Planning & prioritization

Acceptance criteria definition

AI product perspective

Tools

LLM tools

RAG workflows

Job description

Role & responsibilities :

Primary objective: Translate DocTutorials product priorities into clear, valuable and release-ready work across medical-education and other business-priority products.

1. Backlog and Requirement Ownership

• Translate product goals into user journeys, epics, user stories and measurable acceptance criteria.
• Own and continuously refine the backlog based on value, evidence, dependencies and risk.
• Ensure teams understand what is required, why it matters and how success will be measured.
• Make timely scope and priority decisions during execution.

2. Delivery and Validation

• Work daily with Engineering, Design, QA, Academics, Operations and Support.
• Participate in planning, reviews, UAT, release readiness and post-release validation.
• Accept completed work based on outcomes and agreed criteria, not coding completion alone.
• Track adoption, feedback, defects and follow-up improvements.

3. AI Product Ownership

• Define practical requirements for LLM, RAG, search, recommendations and automation use cases.
• Specify data, source traceability, human validation, evaluation and safety expectations.
• Use approved AI tools for research, backlog refinement and analysis with human verification.
• Understand AI limitations and prevent unvalidated outputs from reaching users.