Sr. Architect

Sr. Architect

Full Time only

Experience: 15  t0 18 Years

Job Description: Architect/Sr. Architect - GenAI & Enterprise Architecture (Banking/Insurance)

Role Summary: Architect Leader with 15–18 years of experience in enterprise architecture, engineering leadership, and AI-led transformation. This role is responsible for driving architecture, solutioning, and execution of GenAI initiatives for BFSI (Insurance) clients, while working closely with leadership to deliver large-scale transformation programs.The role combines hands-on architecture leadership, client consulting, and delivery oversight, with a strong focus on operationalizing GenAI (RAG, MCP, Agentic AI) within enterprise environments and embedding AI into the SDLC.

Personal Characteristics

·                15–18 years of experience in technology and architecture roles

• Strong consulting mindset with ability to engage both business and technology stakeholders
• Structured thinker with strong problem-solving and storytelling capabilities
• Ability to bridge strategy, architecture, and execution
• Technically strong with a hands-on approach when needed
• Strong ownership and accountability in a matrixed organization
• Collaborative team player with experience leading distributed teams
• Strong communication skills with ability to influence senior stakeholders

Client Consulting & Delivery

·                Support and co-lead client workshops, architecture discussions, and solutioning sessions

• Translate business problems into AI-enabled architecture and solution blueprints
• Work closely with client stakeholders to define and implement transformation roadmaps
• Contribute to RFP/RFI responses, solution architecture, and effort estimation
• Build strong credibility with both business and technology stakeholders
• Act as a bridge between client business needs and engineering teams

Technical (GenAI) & Architecture Leadership

• Define and drive end-to-end architecture across, Applications, Data platforms, Integration and APIs, Cloud infrastructure, AI/GenAI layers
• Design and implement GenAI-powered solutions, including: RAG (Retrieval-Augmented Generation) pipelines, MCP (Model Context Protocol) connectors for enterprise integrations, Agentic AI systems for workflow automation and decision support
• Build architectures leveraging: Cloud platforms: Azure, AWS, Google Cloud Platform, Vector databases, embeddings, and enterprise data ecosystems
• Ensure architecture decisions address: Scalability, Performance, Security & compliance (Insurance, Asset Management, and Retirement Services regulations), Cost optimization
• Map business use cases to AI/GenAI solutions with measurable outcomes
• Drive adoption of AI across the SDLC, including: AI-assisted code generation, Test automation and defect prediction, Developer productivity tools (Copilot, etc.)
• Support implementation of AI-led engineering practices and platforms
• Improve delivery efficiency, quality, and cycle time using AI and automation

Domain Expertise – BFSI (Insurance)

·                Strong understanding of BFSI domain (Insurance preferred)

• Experience working with core Insurance platforms (Policy, Claims, Underwriting), Asset Management, and Retirement Services systems
• Familiarity with regulatory and compliance requirements in Insurance or BFSI
• Ability to align architecture with domain-specific business priorities

Business Growth & Solutioning Support

·                Support opportunity shaping and solutioning for new and existing accounts

• Contribute to differentiated AI-led solutions for client engagements
• Work with leadership on building reusable assets, accelerators, and frameworks
• Help strengthen technical credibility in client discussions and pursuits
• Drive adoption of best practices, reusable frameworks, and knowledge sharing

Key Skills & Technologies

·                AI/GenAI: LLMs, RAG, MCP Connectors, Agentic AI

·                Cloud Platforms: Azure, AWS, Google Cloud Platform

·                Architecture: Microservices, Distributed Systems, API-first design

·                Data: SQL/NoSQL, Data platforms, Vector DBs

·                DevOps & SDLC: CI/CD, Agile, AI-enabled SDLC tools

·                Programming (working knowledge): Python, Java, or similar