AI Architect
Tech Mahindra
2 - 5 years
Pune City
Posted: 28/06/2026
Job Description
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
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