AI Banking Product Operations Manager (Chennai)

- Santriya Technologies is seeking an AI Banking Product Operations Manager to own operational readiness and performance for banking products, connecting product documentation, front-line workflows, AI tools, controls and measurable customer outcomes. - Product & documentation operating model: You will be assigned one or more company products, client solutions or operational services. - The approved product documentation, SOPs, policies, process maps, knowledge articles, release notes, controls, scripts and AI runbooks are the source of truth. - Use only approved enterprise AI tools to retrieve, summarize, draft, classify, prioritize or automate work. - Validate material AI outputs against current documentation and authoritative system data, record exceptions, and escalate conflicts or missing guidance. - Do not invent product features, prices, customer entitlements, engineering limits, regulatory positions or safety instructions. Key Responsibilities: - Translate product rules and releases into SOPs, knowledge, training, controls and operational acceptance criteria. - Own service, backlog, quality, complaints, incident and exception metrics for assigned products. - Design AI-assisted workflows with transparent permissions, human checkpoints and fallback paths. - Coordinate Product, Engineering, Operations, Risk, Compliance, Legal and Customer Service through changes. - Validate that AI knowledge sources are current, versioned and traceable to approved documentation. - Run post-launch reviews and identify root causes of contact, failure or manual effort. - Maintain risk/control assessments and evidence for material operational changes. - Prioritize automation based on value, risk and customer impact rather than novelty. - AI-enabled ways of working: - Use approved GenAI copilots, enterprise search/RAG, analytics and workflow agents to reduce repetitive work and improve decision preparation. - Keep prompts, outputs and automated actions within approved data-access, confidentiality and retention rules. - Correct inaccurate summaries, classifications or recommendations before they become customer, operational or system records. - Feed recurring AI errors, knowledge gaps and process friction into product, documentation and control improvement. - Human accountability: AI is a copilot, not the accountable decision-maker. - The role holder remains responsible for judgement, quality, privacy, security and appropriate escalation. - Credit, fraud blocking, legal/regulatory, financial advice, safety-critical, clinical, employment and other high-impact decisions must follow delegated authority and required human review. - Success Measures: - Product changes launch with fewer operational defects - Service cost and manual effort decline - Customer and control outcomes improve - Knowledge/SOPs remain aligned to product releases .