Position : AI Solution Architect BFSI | AI & Data.

Role Overview :

We are looking for a seasoned and client-focused Solution Architect with deep expertise in the Banking, Financial Services, and Insurance (BFSI) domain to drive the design and delivery of data-driven, AI-powered, and cloud-native solutions.

This role involves partnering with business and technology stakeholders to translate complex BFSI challenges into scalable, secure, and regulatory-compliant architectures, while supporting digital transformation and innovation initiatives across global financial institutions.

The architect will also play a key role in client engagement, solutioning, and pre-sales efforts, acting as a trusted advisor to senior leadership.

The candidate should be an AI Architect with an end-to-end (E2E) solution architecting approach or an enterprise solutioning approach, capable of designing holistic, scalable solutions across business and technology layers.

Solution Architecture & Design :

- Lead the design of end-to-end technology solutions across BFSI domains including core banking, payments, lending, wealth management, and insurance.

- Translate business requirements into scalable, secure, and compliant architecture blueprints.

- Define architecture across application, data, integration (APIs), cloud, security, and DevOps layers.

- Ensure alignment with enterprise architecture standards and best practices.

- Adopt an E2E solution architecting and enterprise solutioning approach across all engagements.

Data & AI Architecture :

- Architect and drive Data & AI use cases such as fraud detection, AML, credit risk modeling, and customer analytics.

- Design and implement modern data platforms including data lakes, lakehouses, and real-time data pipelines.

- Enable advanced analytics, machine learning, and AI-driven decision-making frameworks.

- Ensure data governance, quality, and compliance across data ecosystems.

- Design AI solutions with an enterprise-wide and end-to-end architectural perspective.

Cloud & Modernization Strategy :

- Architect cloud-native and hybrid solutions leveraging AWS, Azure, or GCP platforms.

- Drive application modernization initiatives using microservices, APIs, and event-driven architectures.

- Enable scalability, resilience, and performance optimization across distributed systems.

- Define DevOps, CI/CD, and automation strategies to accelerate delivery.

CXO Advisory & Stakeholder Engagement :

- Act as a trusted advisor to CXOs and senior stakeholders on technology, data, and AI transformation initiatives.

- Lead architecture discussions, solution workshops, and executive-level presentations.

- Translate complex technical concepts into business-aligned value propositions.

- Support strategic decision-making through technology insights and recommendations.

Pre-Sales & Solutioning :

- Support pre-sales activities including RFP/RFI responses, solution design, and effort estimation.

- Collaborate with sales, consulting, and delivery teams to build compelling, differentiated proposals.

- Define solution narratives, value propositions, and transformation roadmaps.

- Contribute to deal shaping and client presentations for strategic opportunities.

- Demonstrate enterprise solutioning capability with an end-to-end view across business, data, and technology layers.

- Provide architectural governance across the solution lifecycle from design to implementation.

- Identify and mitigate technology risks, ensuring secure and compliant solution delivery.

- Establish best practices for security, data privacy, and regulatory alignment.

Technical Leadership & Delivery Oversight :

- Provide technical leadership and guidance to engineering, data, and platform teams.

- Ensure alignment between architecture design and execution across programs.

- Drive solution quality, performance, and scalability through structured governance.

- Mentor teams and promote adoption of modern engineering and architecture practices.

- Guide teams in implementing E2E architecture aligned with enterprise-wide standards.

BFSI Use Cases :

- Fraud detection, AML, credit risk modeling.

- Customer analytics and personalization.

- Claims automation and underwriting (Insurance).

Required Skills & Experience :

- Strong E2E AI solution architecting experience.

- Python, ML frameworks, GenAI tools (LLMs, LangChain).

- Cloud platforms (AWS/Azure/GCP).

- MLOps tools and microservices architecture.

- 12 to 18 years experience, with AI architecture exposure.