Mastercard

2 days ago

Senior AI Engineer

✓ Verified Job

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

Source: Company careers pageValidated by: Fursa AI

Last checked: 5 minutes agoStatus: Live

Job Summary

Design and lead production-grade generative AI systems for operational intelligence, architecting multi-agent, multimodal, and agentic solutions. Build RAG and Graph-RAG pipelines with vector databases and knowledge graphs, fine-tune and align foundation models, and establish reliable LLMOps/MLOps on Databricks. Develop high-performance Python services for LLM inference orchestration and implement Responsible AI governance for secure, scalable deployment.

Location: Missouri

Workplace: Onsite

Employment Type: Full time

Job Function: Data Science & Machine Learning

Seniority: Mid level

Key Responsibilities

•Architect and lead multi-agent AI systems using frameworks such as LangGraph, CrewAI, and AutoGen for autonomous reasoning and tool use.
•Design and operationalize multimodal generative AI pipelines across text, image, tabular, and graph data using transformer-based architectures.
•Build production-grade RAG and Graph-RAG systems integrating vector databases and knowledge graphs for grounded generation.
•Lead LLM fine-tuning, prompt engineering, and alignment strategies including RLHF, PEFT, LoRA, and instruction tuning.
•Establish robust LLMOps/MLOps pipelines on Databricks and implement Responsible AI governance, including bias detection and safety guardrails.

Pay and Benefits

Salary: USD 115,000 - 184,000 annually

Perks:Health InsuranceDentalVisionLife InsuranceDisability Insurance401kPaid LeaveParental LeavePaid Holidays

Key Requirements

•Master’s or Bachelor’s degree in Computer Science, AI/ML, or Engineering, with hands-on experience delivering complex Gen AI or ML engineering programs in production.
•Expert hands-on experience building and deploying LLM applications, agentic systems, and RAG pipelines from prototype to production.
•Deep proficiency with LLM ecosystems including OpenAI, Anthropic, Gemini, Hugging Face, LangChain/LangGraph, and open-source foundation models (LLaMA, Mistral, Falcon, etc.).
•Strong command of Gen AI engineering patterns including prompt engineering, tool/function calling, vector embeddings, semantic search, and agent memory architectures.
•Excellent Python engineering (async, APIs with FastAPI) plus SQL proficiency, and experience with cloud AI infrastructure and MLOps/LLMOps tooling (e.g., MLflow).

Education:

Skills:AnalyticalCommunicationStakeholder managementEngineering leadershipCross-functional collaboration

Tech Stack:PythonLangGraphCrewAIAutoGenBERTCLIPLLaVAT5WhisperGPT-4oGeminiOpenAIAnthropicHugging FaceLangChainLLaMAMistralFalconPineconePgvector

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

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Mastercard

2 days ago

Senior AI Engineer

✓ Verified Job

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

Source: Company careers pageValidated by: Fursa AI

Last checked: 5 minutes agoStatus: Live

Job Summary

Location: Missouri

Workplace: Onsite

Employment Type: Full time

Job Function: Data Science & Machine Learning

Seniority: Mid level

Key Responsibilities

•Architect and lead multi-agent AI systems using frameworks such as LangGraph, CrewAI, and AutoGen for autonomous reasoning and tool use.
•Design and operationalize multimodal generative AI pipelines across text, image, tabular, and graph data using transformer-based architectures.
•Build production-grade RAG and Graph-RAG systems integrating vector databases and knowledge graphs for grounded generation.
•Lead LLM fine-tuning, prompt engineering, and alignment strategies including RLHF, PEFT, LoRA, and instruction tuning.
•Establish robust LLMOps/MLOps pipelines on Databricks and implement Responsible AI governance, including bias detection and safety guardrails.

Pay and Benefits

Salary: USD 115,000 - 184,000 annually

Perks:Health InsuranceDentalVisionLife InsuranceDisability Insurance401kPaid LeaveParental LeavePaid Holidays

Key Requirements

•Master’s or Bachelor’s degree in Computer Science, AI/ML, or Engineering, with hands-on experience delivering complex Gen AI or ML engineering programs in production.
•Expert hands-on experience building and deploying LLM applications, agentic systems, and RAG pipelines from prototype to production.
•Deep proficiency with LLM ecosystems including OpenAI, Anthropic, Gemini, Hugging Face, LangChain/LangGraph, and open-source foundation models (LLaMA, Mistral, Falcon, etc.).
•Strong command of Gen AI engineering patterns including prompt engineering, tool/function calling, vector embeddings, semantic search, and agent memory architectures.
•Excellent Python engineering (async, APIs with FastAPI) plus SQL proficiency, and experience with cloud AI infrastructure and MLOps/LLMOps tooling (e.g., MLflow).

Education:

Skills:AnalyticalCommunicationStakeholder managementEngineering leadershipCross-functional collaboration

Tech Stack:PythonLangGraphCrewAIAutoGenBERTCLIPLLaVAT5WhisperGPT-4oGeminiOpenAIAnthropicHugging FaceLangChainLLaMAMistralFalconPineconePgvector

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