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