AI Technical Product Manager

AU SMALL FINANCE BANK · Navi Mumbai

  • Experience6–7 yrs
  • SalaryNot disclosed
  • Work modeonsite
  • Levelsenior
  • Posted15 Sept 2026
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About AU SMALL FINANCE BANK

AU SMALL FINANCE BANK is hiring in Navi Mumbai in financial services. This role looks for around 6+ years of experience.

Skills

  • Product management
  • AI agent development
  • Conversational AI
  • Automated lending products
  • Indian BFSI regulations
  • Loan Against Property
  • KYC/AML
  • Underwriting workflows
  • LLM orchestration frameworks
  • LangChain
  • RAG
  • Evaluation pipelines
  • Function calling
  • API integrations
  • FOIR
  • LTV ratios
  • SQL
  • Python
  • Agile

The role

A technical product manager at a financial services company defines AI roadmaps and agentic workflows for lending products, applying Indian BFSI regulations, RAG architectures, and LLM orchestration.

Full job description

About The Role

Job Description – Technical Product Manager

Owns: Agentic journey design , AI roadmap , Use-case prioritization , Customer journey optimization , LLM orchestration priorities , Enterprise Architect , , Integration standards Scalability , Security framework , Customer Journey & Experience , Conversation Experience Lead , Conversational flows , Human-like onboarding journeys multi-agent handoffs , Exception handling ,

Required Experience

Overall Experience: 6+ years in Product Management, with at least 2–3 years explicitly spent building and shipping AI agent, conversational AI, or automated lending products. Domain Expertise: Deep hands-on knowledge of Indian BFSI regulations, specifically Loan Against Property (LAP) guidelines, KYC/AML (Anti-Money Laundering) requirements, and standard underwriting workflows. AI/ML Exposure: Practical experience working with LLM orchestration frameworks (e.g., LangChain), RAG (Retrieval-Augmented Generation) architectures, and evaluation pipelines. Agile Scaling: Proven track record of turning ambiguous user feedback into clear technical specifications, user stories, and acceptance criteria.

Core Skills

Agentic Workflows & Tool Use: Understanding of function calling, orchestrating memory for agents, and API integrations. Underwriting Logic & Credit Systems: Proficiency in translating traditional credit decision matrices (e.g., FOIR, LTV ratios) into agentic algorithms. Data Proficiency: Working knowledge of SQL, Python, or data analytics to trace agent outputs, cost, and latency

Behavioural & Soft Skills

Risk Empathy: Strong bias toward designing transparent, secure, and auditable financial software. Cross-functional Collaboration: Ability to align legal, compliance, engineering, and data scien