Job Description

Role overview

The Product Owner will lead requirements, backlog management and functional delivery for enterprise banking and financial-services platforms.

The role combines product ownership and business analysis, working with business stakeholders, banking domain specialists, architects, engineering and QA teams to translate complex business processes, regulatory requirements and operational needs into clear, implementable product requirements.

The individual should bring a strong understanding of banking operations and be comfortable working across areas such as customer onboarding, KYC, compliance, lending, servicing, workflow automation, operational controls and AI-enabled solutions.

Key responsibilities

- Own and maintain the product backlog, prioritising requirements based on business value, regulatory considerations, dependencies and delivery capacity.

- Lead discovery and requirements workshops with banking business, operations, compliance, risk, credit, legal and technology stakeholders.

- Understand existing business processes and help define target processes, customer and user journeys, operating procedures, roles, approvals, SLAs and exception handling.

- Translate business needs into structured business requirements, process flows, user stories, business rules and measurable acceptance criteria.

- Define requirements for banking workflows including onboarding, customer servicing, KYC, verification, compliance processes, lending, approvals, exceptions and operational reviews.

- Work with banking domain specialists to define product rules, eligibility criteria, validation requirements, decision logic and operational controls.

- Shape user experiences including workbenches, task queues, dashboards, case views and role-specific interfaces.

- Work with architects and engineering teams to define functional requirements for APIs, data exchange, integrations, access controls, audit trails and system dependencies.

- Define requirements for AI-assisted capabilities such as document processing, information extraction, information comparison, knowledge retrieval, report generation, decision support and operational assistance.

- Ensure appropriate human review, controls, explainability and exception-management mechanisms are incorporated into AI-enabled processes.

- Maintain requirements traceability and provide functional clarification throughout design, development, testing and implementation.

- Support backlog refinement, sprint planning and prioritisation in collaboration with engineering and delivery teams.

- Coordinate business validation and UAT, assess defects against agreed requirements and acceptance criteria, and support release readiness.

- Support phased releases, operational handover, user documentation, training and adoption activities.

- Manage changes to requirements and clearly communicate implications for scope, effort, dependencies, timelines and business outcomes.

- Identify opportunities to simplify processes, reduce manual effort and improve control effectiveness through workflow automation and AI.

Required experience and skills

- Typically 10+ years of experience in business analysis, product ownership or functional consulting, including 4+ years owning a product backlog or leading functional delivery.

- Experience delivering enterprise technology solutions within banking or financial services.

- Good understanding of banking processes, operations and controls.

- Exposure to areas such as customer onboarding, KYC, compliance, payments, lending, credit, servicing,



operations or financial crime processes.

- Robust hands-on requirements analysis and documentation skills, including process modelling, user stories, business rules and acceptance criteria.

- Experience with workflow automation, case management, approvals, exception management, role-based access, SLAs and audit requirements.

- Ability to understand APIs, data models, integrations and system interactions sufficiently to define functional behaviour and work effectively with technical teams.

- Experience working with Agile delivery teams, including backlog refinement, sprint planning, demonstrations, UAT and production releases.

- Strong stakeholder-management and workshop-facilitation skills.

- Ability to work with senior business, operations and technology stakeholders and translate between business and technical teams.

- Ability to challenge unclear requirements, resolve conflicting priorities and maintain scope discipline.

- Strong analytical, problem-solving and written communication skills.

- Working knowledge of tools such as Jira or Azure Dev Ops, Confluence and process-modelling applications.

Preferred experience

- Experience across one or more banking domains such as retail banking, corporate banking, lending, payments, wealth management, financial crime, compliance or banking operations.

- Exposure to customer onboarding, KYC, due diligence and regulatory-control processes.

- Experience with lending, credit assessment, underwriting or product-management workflows.

- Experience designing or implementing enterprise workflow and case-management solutions.

- Experience with AI-enabled document processing, knowledge assistants, intelligent workflow automation, decision-support systems or generative AI applications.

- Understanding of long-running business processes involving multiple systems, teams and human approvals.

- Familiarity with banking security, privacy, regulatory compliance, auditability and operational-resilience requirements.

- Experience with target operating models, process transformation, change management or technology-enabled business transformation.

- Exposure to cloud, data and integration architectures used within banking environments.

Expected outcomes

The Product Owner will be expected to:

- Maintain a prioritised and implementation-ready product backlog.

- Provide explicit requirements and acceptance criteria that reduce ambiguity and development rework.

- Establish alignment between business objectives, banking controls and technology implementation.

- Improve collaboration between business, domain, architecture, engineering and QA teams.

- Support predictable and controlled delivery across product releases.

- Ensure appropriate business validation and operational readiness before production deployment.

- Help identify measurable improvements in processing time, manual effort, operational visibility, control effectiveness and user adoption.

Qualification

CSPO Certification
Should be open to travel.

Requirements
Key Responsibilities Develop and maintain enterprise AI applications powered by Anthropic Claude models. Design, build,



and optimize inference pipelines for production AI workloads. Integrate Claude APIs into enterprise applications and backend systems. Design and implement Retrieval-Augmented Generation (RAG) solutions using vector databases. Build AI agents and agentic workflows using modern orchestration frameworks. Develop scalable backend services and REST APIs using Python. Implement prompt engineering strategies for different business use cases. Optimize AI application performance for latency, throughput, reliability, and cost. Build reusable AI components, libraries, and integration frameworks. Collaborate with cross-functional teams to translate business requirements into technical solutions. Integrate AI applications with enterprise systems, APIs, and databases. Implement monitoring, logging, evaluation, and observability for AI applications. Troubleshoot production issues and continuously improve platform performance. Follow enterprise security, governance, and responsible AI best practices. Participate in code reviews, technical discussions, and architecture planning. Required Skills & Qualifications 6–8 years of experience in Software Engineering or Backend Development. Minimum 2 years of hands-on experience working with Large Language Models (LLMs) and Generative AI. Strong hands-on experience with Anthropic Claude APIs and enterprise AI integrations. Proficiency in Python. Experience building REST APIs using FastAPI, Flask, or similar frameworks. Strong understanding of: Large Language Models (LLMs) Prompt Engineering Retrieval-Augmented Generation (RAG) AI Agents and Agentic Workflows Embeddings and Semantic Search Experience with AI orchestration frameworks such as: Lang Chain Lang Graph Semantic Kernel Experience working with vector databases such as: Pinecone ChromaDB Weaviate Milvus FAISS Experience integrating AI applications with enterprise platforms and APIs. Valuable understanding of cloud platforms such as Microsoft Azure or Amazon Web Services (AWS). Familiarity with Git, Docker, Kubernetes, and CI/CD pipelines. Strong analytical, debugging, and problem-solving skills. Excellent communication and collaboration abilities. Preferred Skills Experience building AI copilots or conversational AI solutions. Experience developing multi-agent AI systems. Familiarity with Model Context Protocol (MCP). Experience with Azure AI Foundry or Azure OpenAI Services. Knowledge of AI evaluation and observability tools such as Langfuse, Phoenix, or Open Telemetry. Exposure to Redis, Kafka, or event-driven architectures. Understanding of AI guardrails, responsible AI, and enterprise security practices. Experience with Dev Ops and MLOps concepts for AI deployments. Technical Skill Set Programming Languages Python SQL AI & Generative AI Anthropic Claude Prompt Engineering Retrieval-Augmented Generation (RAG) AI Agents Lang Chain Lang Graph Semantic Kernel Backend Technologies FastAPI Flask REST APIs Microservices Databases PostgreSQL Pinecone ChromaDB Weaviate Milvus FAISS Cloud Platforms Microsoft Azure Amazon Web Services (AWS) Dev Ops & Tools Git Docker Kubernetes CI/CD Pipelines Monitoring & Observability Langfuse Open Telemetry Phoenix (Preferred) Qualifications Bachelor's degree in Computer Science, Information Technology, Engineering, or a related field. Master's degree is an advantage but not mandatory. Preferred Certifications Azure AI Engineer Associate (AI-102) Azure Fundamentals (AZ-900) AWS Certified Machine Learning – Specialty (Preferred) Anthropic Claude Certification or equivalent Generative AI certification (Preferred)

📌 Product Owner – Banking Workflow and AI Platforms (India)
🏢 Latent Bridge
📍 India