AI / ML Architect / Engineering Leader

About the Role :

We’re looking for a Technology Leader in AI / ML and Generative AI with strong experience in architecting, designing, and delivering enterprise-grade AI platforms . The ideal candidate will combine deep hands-on expertise in LLMs, RAG, Agentic AI, and Azure AI Services with enterprise architecture and engineering leadership skills.

You will drive the AI-first transformation journey for large enterprises, build AI-powered digital expert systems , and lead teams to deliver scalable, secure, and business-aligned AI solutions.

Key Responsibilities :

Architect and implement AI / ML and Generative AI platforms for large-scale enterprise adoption.

Design and productionize AI-powered systems for Banking use cases such as onboarding, payments, and cash management.

Develop RAG pipelines, Agentic AI workflows , and LLMOps frameworks using LangChain, LangGraph, and Hugging Face.

Integrate solutions with Core Banking, ERP, H2H, and API platforms ensuring scalability, security, and compliance.

Lead and mentor high-performing engineering teams following Agile / DevOps best practices.

Evaluate and integrate emerging AI ecosystems (OpenAI, Anthropic, Mistral, Azure OpenAI, GCP Vertex AI).

Collaborate with product and business leaders to align AI initiatives with enterprise strategy and measurable ROI.

Technical Skills & Expertise :

Generative AI & LLMs : GPT-4, LLaMA, Claude, RAG, Agentic AI, LangChain, LangGraph, LlamaIndex

AI / ML Engineering : Deep Learning, NLP, Python, FastAPI, MLFlow, PyTorch, TensorFlow, Keras

Cloud & Platform Engineering : Azure AI Services, Azure OpenAI, Synapse, Azure ML Studio, AWS, GCP

Data & Integration : Kafka, ETL pipelines, APIs, vector DBs (Chroma, Pinecone, Azure AI Search)

Architecture : Cloud-native, microservices, event-driven systems, Kubernetes, Docker, CI / CD

Why Join :

Drive end-to-end AI / GenAI transformation across global BFSI clients

Lead high-impact AI innovation and modernization programs

Work with cutting-edge AI ecosystems and enterprise-grade LLM deployments