Lead Generative AI & ML Engineer

About the role

Mastercard's Business & Market Insights (B&MI) group is seeking a Lead Engineer to drive its Generative AI and Machine Learning initiatives within the Operational Intelligence Program. This senior technical leader will shape the architecture and delivery of next‑generation large language model (LLM) and multimodal AI systems that power enterprise‑scale decision making.

Key responsibilities

• Architect and lead multi‑agent AI systems using frameworks such as LangGraph, CrewAI, and AutoGen.
• Design and operationalize multimodal generative AI pipelines that combine text, image, tabular, and graph data with transformer models (BERT, CLIP, LLaVA, T5, Whisper, GPT‑4o, Gemini).
• Build production‑grade Retrieval‑Augmented Generation (RAG) and Graph‑RAG solutions integrating vector stores (Pinecone, pgvector, OpenSearch) and knowledge graphs (Neo4j, AWS Neptune).
• Lead LLM fine‑tuning, prompt engineering, and model alignment using RLHF, PEFT, LoRA, and instruction tuning.
• Establish robust LLMOps and MLOps pipelines on Databricks (AWS) with MLflow, feature stores, model lineage tracking, and continuous retraining.
• Develop high‑performance Python backend services for LLM inference orchestration, async job handling, streaming responses, and distributed data processing.

Required profile

• Proven experience leading AI/ML engineering teams in an enterprise environment.
• Deep expertise in generative AI, large language models, and multimodal AI architectures.
• Strong background in building scalable, production‑grade AI systems.

Required skills

• Python
• LangGraph, CrewAI, AutoGen
• Transformer models: BERT, CLIP, LLaVA, T5, Whisper, GPT‑4o, Gemini
• Vector databases: Pinecone, pgvector, OpenSearch
• Knowledge graphs: Neo4j, AWS Neptune
• LLM fine‑tuning techniques: RLHF, PEFT, LoRA, instruction tuning
• Databricks (AWS), MLflow, feature stores
• LLMOps / MLOps pipelines