Role Definition

Own the performance, reliability, and continuous improvement of AI chatbots supporting MineStar digital applications.

This role ensures high quality AI behavior by monitoring GenAI performance, detecting and reducing hallucinations, governing system prompts, and improving knowledge inputs. The AI Product Owner works closely with GenAI platform teams, SMEs, Data owners, and Product Support to refine prompts, tune chatbot settings, and evolve AI capabilities to deliver accurate and trusted responses.

Responsibilities

• AI Bot Performance Ownership:
  Own chatbot performance across accuracy, quality, efficiency, and response reliability; proactively identify performance degradation.

• Hallucination Detection Control:
  Monitor AI responses, identify hallucinations and incorrect outputs, and define corrective actions to reduce risk and improve trust.

• System Prompt Configuration Management:
  Create, edit, tune, and govern system prompts and custom chatbot settings, including version control, guardrails, uncertainty handling, and escalation logic.

• GenAI Platform Requirements:
  Translate observed gaps and performance issues into clear improvement requirements for GenAI platform teams.

• Knowledge Input Improvement:
  Improve chatbot response quality by refining, structuring, and updating knowledge articles and source inputs used by the AI.

• Agent Validation Testing:
  Define and execute validation plans; perform end to end functional and non functional testing before general availability.

• Application Specific Ownership:
  Own AI bot behavior for at least one MineStar application (Fleet, Health, Terrain, or Command), ensuring domain correctness.

• Source Data Governance:
  Identify, curate, add/remove/update/purge source data; maintain metadata, versioning, freshness, and single source of truth.

• Support Incident Governance:
  Triage and resolve AI related issues; coordinate fixes with SMEs, Data owners, and GenAI teams; execute rollback plans when quality degrades.

• Cross Team Collaboration:
  Resolve dependencies across Product, GenAI, Data, and Support teams to ensure stable chatbot operations.

Immediate Priorities (First 12 Months)

• Establish baseline bot performance and hallucination metrics .

• Stabilize and govern system prompts and chatbot configurations .

• Improve AI accuracy through better knowledge article inputs .

• Create structured feedback loops with GenAI platform teams.

• Achieve production ready bots with clear rollout and rollback processes.

Success Metrics

• Reduction in hallucinations and incorrect responses

• Improvement in chatbot accuracy, relevance, and quality scores

• Stability of bot performance across releases

• Faster turnaround on AI defects and enhancements

• Stakeholder confidence in chatbot behavior

Degree Requirement

Required Qualifications:

• Bachelor s degree in Engineering , Computer Science, Data Science, or related field.

• 8-12+ years of experience in product ownership, digital platforms, or AI enabled systems.

• Hands on experience working with GenAI chatbots or AI agents in production.

• Proven experience editing, governing, and tuning system prompts and AI settings .

• Strong understanding of AI validation, testing, and hallucination risks.

• Experience collaborating with GenAI platform , Data, Support, and SME teams.

• Strong analytical skills and clear communication abilities.

Preferred Qualifications:

• Experience with MineStar applications (Fleet, Health, Terrain, Command)

• Background in Product Support or Operations

• Experience evaluating AI behavior and response quality

• Familiarity with enterprise knowledge management practices

• Prior work with centralized GenAI platform teams

Top Skills:

• AI chatbot performance management

• Hallucination detection and mitigation

• System prompt design and tuning

• AI validation and quality assurance

• Knowledge content structuring for AI consumption

• Backlog prioritization and requirements definition

Location

• Bangalore or Chennai

• On site role (no remote option )

• No travel expected

Key Competencies

• Strong ownership and accountability for AI outcomes

• Bias for quality, safety, and user trust

• Structured problem solving in ambiguous AI systems

• Continuous improvement mindset

• Clear communicator across technical and non technical teams

• High reliability and follow through