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Job Description & How to Apply Below
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 (Lang Graph, Lang Chain)
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 (Lang Graph, Lang Chain)
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:
Open Search / Vector DBs
Vault (secure data access)
Streaming / batch pipelines
4. Cloud, Dev Ops & 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
Open Search / Elastic Search
Grafana / Prometheus
Hashi Corp 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
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