# Senior AI Engineer, Generative AI & ML Engineering **Company**: Mastercard **Location**: Pune, India **Experience**: senior **Job type**: full-time **Category**: Engineering **Industry**: Finance **Apply**: https://mastercard.wd1.myworkdayjobs.com/en-US/CorporateCareers/job/Pune-India/AI-Engineer-II_R-294112?utm_source=yubhub.co&utm_medium=jobs_feed&utm_campaign=apply **Canonical**: https://yubhub.co/jobs/job_6c2b6990-bba ## Description Mastercard's Business & Market Insights (B&MI) group is seeking a Senior AI Engineer, Generative AI & ML Engineering, for the Operational Intelligence Program within B&MI. In this hands-on role, you'll design, build, and ship production-grade agentic AI systems. These include agents that make extensive tool calls into enterprise services and APIs, handle complex multi-step workflows, and deliver secure, scalable, reliable results. Responsibilities: - Architect and build the tool-calling layer that powers our agents: wrap internal services, data platforms, and external APIs as well-defined tools with clear schemas, contracts, and permissions. - Engineer reliable tool execution at scale, including parallel and chained tool calls, timeouts, retries, idempotency, error recovery, and graceful handling of tool failures or bad model outputs. - Develop high-performance Python backend services for LLM orchestration, covering async job handling, streaming responses, caching, rate limiting, and distributed workflows supporting high-throughput Gen AI operations. - Engineer state, memory, and context management subsystems so agents can maintain session continuity across long, multi-step, tool-heavy interactions. - Architect multi-agent and skills-based agent systems using frameworks such as LangGraph, CrewAI, AutoGen, or similar, enabling autonomous reasoning, tool use, inter-agent coordination, and adaptive decision-making at enterprise scale. - Build observability for agent behavior, including end-to-end tracing of tool calls, measuring tool-selection accuracy, and debugging multi-step agent runs in production. - Build retrieval systems (RAG and Graph-RAG) where agents need grounded knowledge, using vector databases (e.g., Pinecone, pgvector, OpenSearch) and knowledge graphs (e.g., Neo4j, AWS Neptune). - Establish LLMOps and MLOps pipelines on Databricks (AWS), covering MLflow, prompt and agent evaluation, model lineage tracking, CI/CD, and monitoring. - Design multimodal generative AI pipelines that unify text, image, tabular, and graph data using modern transformer-based and foundation models. - Guide fine-tuning, prompt engineering, and alignment strategies (e.g., PEFT, LoRA, instruction tuning, RLHF) to adapt foundation models for specialized enterprise use cases, working closely with ML specialists. - Implement Responsible AI practices, including hallucination mitigation, bias detection, output safety guardrails, explainability, and compliance with data ethics standards. - Evaluate and productionize advances in agentic AI, multimodal models, and frontier foundation models, benchmarking them against enterprise performance and safety requirements. - Lead, mentor, and grow a team of engineers, and set the engineering standard for Gen AI development across the program. Requirements: - Bachelor's or Master's degree in Computer Science, AI/ML, or Engineering, or equivalent practical experience. - A strong track record of building and operating production backend systems at scale, including distributed services, APIs, async processing, data stores, and observability. - Strong API design and integration experience: you know how to build services that other systems, and now LLMs, can call safely and reliably. - Excellent Python engineering skills, including async programming, API development (FastAPI or similar), and microservices, plus SQL proficiency. - Hands-on experience shipping at least one LLM-powered application to production that uses tool/function calling, such as agents that call APIs, query databases, or trigger workflows. - A working understanding of Gen AI engineering patterns, such as prompt design, embeddings, semantic search, and agent memory, or a demonstrated ability to ramp up quickly on new technical domains. - Experience with at least one cloud platform (AWS preferred; Azure or GCP welcome). - Experience leading or mentoring engineers, plus strong communication and stakeholder management skills. ## Skills ### Required - Python - AI/ML - Backend Engineering - API Design - Distributed Systems - Async Programming - SQL - Gen AI - LLMs - MLOps ### Nice to have - Model Context Protocol (MCP) - building tool servers and connectors for LLM agents - evaluating agent performance - fine-tuning - multimodal models - knowledge graphs - MLOps tooling like MLflow, Weights & Biases, SageMaker, or Bedrock --- Source: [Apply at mastercard.wd1.myworkdayjobs.com](https://mastercard.wd1.myworkdayjobs.com/en-US/CorporateCareers/job/Pune-India/AI-Engineer-II_R-294112?utm_source=yubhub.co&utm_medium=jobs_feed&utm_campaign=apply)