Mastercard

2 months ago

AI Engineer

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 4 hours agoStatus: Live

Job Summary

Lead engineering for Mastercard's Gen AI and ML initiatives within the Operational Intelligence Program. You will architect multi-agent AI systems, design multimodal AI pipelines, build production-grade RAG/Graph-RAG solutions, lead LLM fine-tuning and MLOps, and develop high-performance Python backends to enable scalable, secure AI delivery across enterprise-scale use cases.

Location: Pune

Workplace: Onsite

Employment Type: Full time

Job Function: Data Science & Machine Learning

Key Responsibilities

•Architect and lead the development of multi-agent AI systems using LangGraph, CrewAI, and AutoGen for enterprise-scale autonomous reasoning and coordination.
•Design and operationalize multimodal generative AI pipelines unifying text, image, tabular, and graph data with transformer architectures.
•Build production-grade RAG and Graph-RAG systems with vector databases and knowledge graphs for semantic retrieval and grounded generation.
•Lead LLM fine-tuning, prompt engineering, and model alignment (RLHF, PEFT, LoRA, instruction tuning) for specialized enterprise use cases.
•Establish robust LLMOps and MLOps pipelines on Databricks (AWS) with MLflow, feature stores, evaluation frameworks, and continuous retraining workflows.

Key Requirements

•Master's or Bachelor's degree in Computer Science, AI/ML, or Engineering.
•Hands-on experience designing, building, and deploying large language model (LLM) applications, agentic systems, and RAG pipelines in production.
•Proficiency with ML fundamentals (predictive modeling, deep learning) and experience with PyTorch or TensorFlow.
•Excellent Python engineering skills including async programming, API development (FastAPI), and building inference-ready microservices; SQL proficiency.
•Hands-on experience with cloud AI infrastructure (AWS SageMaker/Bedrock, Azure OpenAI, or GCP Vertex AI) and familiarity with MLOps/LLMOps tools (MLflow, Weights & Biases).

Experience:AI/MLGen AILLMRAGMultimodalProduction

Education:Master's

Skills:CommunicationLeadershipProblem-solvingTeamStakeholder management

Languages:English

Tech Stack:LangGraphLangChainCrewAIAutoGenBERTCLIPLLaVAT5WhisperGPT-4oGeminiPineconePgvectorOpenSearchNeo4jAWS NeptuneRLHFPEFTLoRADatabricks

Company Brief

Mastercard

Mastercard is a global payments and technology company that processes transactions, provides fraud prevention and data services, and builds payment infrastructure for consumers, businesses, merchants and governments across 200+ countries.

Industry: Payments

Company Size: Enterprise (1,001+ employees)

Revenue: USD 1B+

Growth: Public Company

Valuation: Public Company (Market Cap in USD)

Funding: IPO / Publicly Listed

Headquarters: Purchase, New York, United States

Founded: 1966

Glassdoor: 4.1

Website LinkedIn Glassdoor

Loading job details...

Preparing the role view and application actions.

Mastercard

2 months ago

AI Engineer

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 4 hours agoStatus: Live

Job Summary

Location: Pune

Workplace: Onsite

Employment Type: Full time

Job Function: Data Science & Machine Learning

Key Responsibilities

•Architect and lead the development of multi-agent AI systems using LangGraph, CrewAI, and AutoGen for enterprise-scale autonomous reasoning and coordination.
•Design and operationalize multimodal generative AI pipelines unifying text, image, tabular, and graph data with transformer architectures.
•Build production-grade RAG and Graph-RAG systems with vector databases and knowledge graphs for semantic retrieval and grounded generation.
•Lead LLM fine-tuning, prompt engineering, and model alignment (RLHF, PEFT, LoRA, instruction tuning) for specialized enterprise use cases.
•Establish robust LLMOps and MLOps pipelines on Databricks (AWS) with MLflow, feature stores, evaluation frameworks, and continuous retraining workflows.

Key Requirements

•Master's or Bachelor's degree in Computer Science, AI/ML, or Engineering.
•Hands-on experience designing, building, and deploying large language model (LLM) applications, agentic systems, and RAG pipelines in production.
•Proficiency with ML fundamentals (predictive modeling, deep learning) and experience with PyTorch or TensorFlow.
•Excellent Python engineering skills including async programming, API development (FastAPI), and building inference-ready microservices; SQL proficiency.
•Hands-on experience with cloud AI infrastructure (AWS SageMaker/Bedrock, Azure OpenAI, or GCP Vertex AI) and familiarity with MLOps/LLMOps tools (MLflow, Weights & Biases).

Experience:AI/MLGen AILLMRAGMultimodalProduction

Education:Master's

Skills:CommunicationLeadershipProblem-solvingTeamStakeholder management

Languages:English

Tech Stack:LangGraphLangChainCrewAIAutoGenBERTCLIPLLaVAT5WhisperGPT-4oGeminiPineconePgvectorOpenSearchNeo4jAWS NeptuneRLHFPEFTLoRADatabricks

Company Brief

Mastercard

Industry: Payments

Company Size: Enterprise (1,001+ employees)

Revenue: USD 1B+

Growth: Public Company

Valuation: Public Company (Market Cap in USD)

Funding: IPO / Publicly Listed

Headquarters: Purchase, New York, United States

Founded: 1966

Glassdoor: 4.1

Website LinkedIn Glassdoor