Job highlights

- 7-12 years experience with deep expertise in Core Banking systems (Finacle, Temenos T24, FLEXCUBE, BaNCS), AI-driven banking solutions, KYC, AML, credit risk, fraud detection, and regulatory compliance
- Lead discovery and design of AI banking solutions, translate business needs into technical specs for AI/ML teams, manage AI lifecycle requirements, ensure compliance and domain alignment

Job Summary Job Title: Senior Business Analyst - Banking. Experience: 7-12 Years. Category: Business Analyst. Shift: 8:30 AM to 6:00 PM. Work Mode: Hybrid (3 days in office, 2 days WFH).

Primary location: Bangalore. Employment Type: Full Time. Education Qualification: Bachelor's degree in Computer Science or related field or higher with minimum 3 years of relevant experience.

Your future duties and responsibilities

We are looking for a Business Functional Analyst who sits at the intersection of Core Banking and Artificial Intelligence. In this role, you will lead the discovery and design of AI driven banking solutions. You will be responsible for translating complex business needs into technical specifications for data scientists and ML engineers, ensuring that every AI model built-from LLMs to Agentic workflows-solves a concrete banking problem while adhering to strict compliance and operational standards.

- Lead the discovery and design of AI driven banking solutions.
- Translate complex business needs into technical specifications for data scientists and ML engineers, ensuring that every AI model built-from LLMs to Agentic workflows-solves a concrete banking problem while adhering to strict compliance and operational standards.
- Requirements Engineering for AI.
- Translate Ambiguity:



Elicit requirements for AI/ML applications and translate them into actionable User Stories with rigorous Acceptance Criteria.
- AI Life Cycle Management: Define functional requirements across the ML lifecycle, from data ingestion and labeling to model monitoring (MLOps).
- RAG & Agentic Design: Work with stakeholders to define the knowledge base and retrieval logic for RAG based systems and the decision making boundaries for AI Agents in banking workflows.
- Banking & Domain Alignment.
- Domain Expertise: Apply deep Core Banking knowledge to ensure AI solutions align with retail/commercial banking processes (e.g., credit scoring, KYC, fraud detection, or customer service).
- Compliance & Risk: Ensure user stories include non functional requirements for AI transparency, bias mitigation, and regulatory reporting.

Required qualifications to be successful in this role Must-Have Skills

- Banking Domain
- Core Banking Systems (Finacle, Temenos T24, FLEXCUBE, BaNCS)
- Retail Banking & Commercial Banking processes
- KYC (Know Your Customer)
- AML (Anti-Money Laundering)
- Credit Risk / Credit Scoring
- Lending & Loan Origination
- Fraud Detection
- Customer Onboarding
- Regulatory Compliance in Banking
- Business Analysis
- Requirements Gathering & Elicitation
- Business Requirement Documents (BRD)
- Functional Requirement Specifications (FRS)
- User Stories & Acceptance Criteria
- Gap Analysis
- Process Mapping (BPMN, Process Flows)
- Stakeholder Management
- Agile / Scrum Methodology

Positive-to-Have Skills

- Technical Understanding
- Python (basic understanding)
- Machine Learning Models
- NLP (Natural Language Processing)
- MLOps Concepts
- Azure AI Services
- AWS AI/ML Services
- Microsoft Copilot
- OpenAI / Azure OpenAI

Skills

- Agentic AI
- Agentic RAG
- Agile
- AI Data Modeling
- Banking

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