Role Summary
A hands-on technical authority responsible for the end-to-end design, implementation, and governance of enterprise-grade GenAI solutions (LLMs, RAG, Agentic AI) specifically for the Financial Services domain.
Key Responsibilities
- Architectural Leadership: Define blueprints for RAG, AI Agents, and model fine-tuning; evaluate LLMs, vector databases (Pinecone, Weaviate), and frameworks (LangChain, LlamaIndex).
- Hands-on Development: Build production-grade POCs and prototypes; integrate AI with enterprise systems (CRM/ERP) via microservices.
- Governance & Compliance: Ensure solutions meet strict financial regulations (GDPR/HIPAA) and implement Responsible AI (bias mitigation, toxicity filtering).
- LLMOps: Standardize automated deployment, monitoring (drift/hallucination), and CI/CD pipelines for AI.
- Strategic Advisory: Consult with C-level executives on AI roadmaps and mentor technical teams.
Required Qualifications
- Experience: 10+ years in Solution/Data Architecture, with 5+ years specifically in GenAI/LLM production systems.
- Technical Mastery (MUST):
- Deep expertise in RAG, Agentic AI, and LLM fine-tuning.
- Proven deployment of diverse models (GPT, Claude, Llama, Gemini).
- Expertise in Python and frameworks like LangChain or AutoGen.
- Proficiency in at least one major cloud (AWS, Azure, or GCP).
- Domain Expertise (MUST): Solid background in Financial Services (Banking, Insurance, or FinTech) and its regulatory landscape.
- Tools: Mastery of vectorization, containerization (Docker/Kubernetes), and MLOps tools.
