AI Architect

Role: AI Architect – BFSI (Banking & Financial Services)

Experience: 12+ years

Location: Pune, Hyderabad preferably

Domain: Banking

Notice Period: within 60 Days

Role Overview

We are looking for a strategic AI Architect to design and scale enterprise-grade AI solutions for BFSI clients, with a strong focus on agentic AI, GenAI platforms, and domain-specific intelligence. This role combines deep technical expertise with banking domain understanding to drive secure, compliant, and high-impact AI transformations.

Required Skills & Experience

Core AI & Architecture

• 12+ years in enterprise architecture / solution architecture
• Strong expertise in:

Generative AI & LLMs

Agentic AI frameworks (LangGraph, LangChain)

RAG, prompt engineering, vector search

• Experience designing production-grade AI platforms

Key Responsibilities

1. Enterprise AI Architecture (BFSI-Focused)

• Define end-to-end AI architecture blueprints for banking use cases (e.g., underwriting, fraud detection, customer service, KYC/AML)
• Design agentic AI ecosystems (multi-agent orchestration, decisioning workflows)
• Develop domain-specific LLM/SLM architectures aligned to BFSI data models
• Ensure architecture adheres to regulatory and compliance requirements (RBI, MAS, etc.)

2. GenAI & Agentic AI Solution Design

• Architect solutions using:
• LLMs (OpenAI, Llama, etc.)
• Agent frameworks (LangGraph, LangChain)
• RAG pipelines with enterprise data sources
• Design intelligent workflows:
• Autonomous decisioning agents
• Human-in-the-loop systems
• Policy-aware AI assistants
• Enable context-aware, explainable AI for regulated environments

3. Data & Platform Architecture

• Define architecture for:
• Data ingestion, governance, and vectorization
• Knowledge graphs and semantic layers for BFSI
• Integrate with enterprise platforms:
• Core banking systems
• CRM / LOS / LMS systems
• Risk & compliance platforms
• Leverage tools such as:
• OpenSearch / Vector DBs
• Vault (secure data access)
• Streaming / batch pipelines

4. Cloud, DevOps & Scalability

• Architect cloud-native AI solutions on AWS / Azure / GCP
• Ensure:
• Scalable microservices-based architecture
• Deployment via Docker & Kubernetes
• CI/CD pipelines for AI models and agents
• Design observability using:
• Grafana, Prometheus
• AI telemetry and monitoring pipelines

5. AI Governance, Risk & Compliance

• Establish Responsible AI frameworks:
• Model transparency, fairness, explainability
• Ensure compliance with:
• AI Regulatory guidelines, GDPR, and data privacy regulations
• Implement:
• Model risk management
• Auditability and traceability
• Secure AI lifecycle governance

6. Leadership & Client Engagement

• Partner with CIOs, Chief Data Officers, and business stakeholders
• Lead architecture discussions in RFPs and transformation programs
• Mentor engineering and data science teams
• Drive reusable AI accelerators and frameworks

Technology Stack

• Programming: Python (must-have)
• APIs & backend: FastAPI / microservices
• Platforms:

Kubernetes, Docker

OpenSearch / ElasticSearch

Grafana / Prometheus

HashiCorp Vault

• Cloud:

AWS / Azure / GCP AI services

Preferred Qualifications

• Experience building AI CoEs or enterprise AI platforms
• Exposure to domain-specific SLMs for banking
• Experience in regulator-facing AI programs
• Strong understanding of data governance and lineage frameworks