Lead AI Software Engineer
- Mastercard
- 10 - 12 years
- Pune
- 2 months ago
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Job Description
- As the engineering team of Treasury Service, we are directly responsible for moving billions of dollars in domestic and cross-border currencies worldwide daily between our customers
- We are an agile development organization with teams distributed globally across technology hubs in the U S , India, and Ireland
- Were looking for a senior technical leader to drive our AI initiativesfrom building high-impact Proofs of Concept (PoCs) to productionizing Model Control Protocols (MCPs), evolving our AI framework, and supporting the drive to AI adoption across the entire Payment Network
- You'll own technical design, implementation, and collaborate cross-functionally to deliver scalable, secure, and reliable AI-powered systems using Python and TypeScript.
- Roles:All staff at Mastercard are expected to demonstrate ''Mastercard Way'' cultural values daily - Create Value, Grow Together, Move Fast. As a Lead Software Engineer at Mastercard, you are expected to perform the following general duties:Were looking for a senior technical leader to drive our AI initiativesfrom building high-impact Proofs of Concept (PoCs) to productionizing Model Control Protocols (MCPs), evolving our AI framework, and supporting the drive to AI adoption across the entire Payment Network.
- Youll own technical design, implementation, and collaborate cross-functionally to deliver scalable, secure, and reliable AI-powered systems using Python and TypeScript.
Responsibilities:
- Architecture & Leadershipo Own end-to-end architecture of AI services, data pipelines, and inference systems.o Design and implement MCPs, AI Agents, AI Workflow (or similar orchestration/control layers) to standardize model lifecycle, governance, and observability.
- Lead PoCs from ideation design build evaluation handoff to production teams.o Establish engineering best practices (code quality, testing, CI/CD, security) according to Mastercard standard. Framework Developmento Enhance and modularize existing AI components (e.g., MCs, Prompts).
- Build reusable SDKs and TypeScript APIs for product teams to integrate AI reliably
- Optimize performance and cost (batch vs. streaming, GPU/CPU utilization, caching, quantization, distillation). Modeling & Integrationo
- Work with AI engineers/data scientists on model selection, fine-tuning, prompt engineering, guardrails, and evaluation.o Integrate LLMs/Transformers with application logic (retrieval, grounding, tool-use, function calling).o Implement vector search and retrieval-augmented generation (RAG), including data curation and evaluation. Operational Excellenceo Ensure compliance with security & privacy (PII handling, role-based access, auditability).Partner with Product, Security, and Compliance to meet business and regulatory requirements.
- Qualifications:
- Education/Experience: 10-12+ years in software engineering with 3-5+ years in AI/ML systems; or equivalent track record delivering production AI systems at scale. Languages: Expert in Python (data/ML, services) and TypeScript (APIs, SDKs, tooling).
- Framework: Hands-on FastMCP, Dyad.sh, N8N, or similar ecosystems; experience with LLMs and Transformers. Backend & APIs: Strong with FastAPI/Flask/Django; REST/GraphQL API design, authentication/authorization (OAuth2, JWT), rate limiting, and performance tuning. Cloud & DevOps: Proficient with AWS/Azure, Docker, Kubernetes, IaC (Terraform/CloudFormation), and CI/CD (GitHub Actions/GitLab CI). Data & Retrieval:
- Experience with ETL/data pipelines (Airflow/Flyte/Prefect), object storage, feature stores, and vector databases (pgvector, Weaviate).
- Testing & Quality: Unit/integration tests for ML and services; model evaluation frameworks; can define SLAs/SLOs for AI systems. Security & Governance: Practical knowledge of data privacy, model governance, and secure secrets management
- Preferred/Bonus Skills Experience designing MCPs (or comparable orchestration/control protocols) for model lifecycle and policy enforcement.
- Prompt engineering, RAG, grounding with enterprise data, and safety/guardrail frameworks. Performance engineering: quantization, distillation, ONNX/TensorRT, GPU scheduling. Event-driven systems (Kafka/PubSub), streaming inference, and cost-aware autoscaling.
- Familiarity with LangChain, LlamaIndex, OpenAI/Azure OpenAI, bedrock, or on-prem LLM serving (vLLM/Triton
- Core Competencies Systems Thinking: Designs for scale, reliability, and maintainability; clear tradeoff communication.
- Technical Leadership: Mentors engineers, raises the bar on design reviews and code quality. Product Mindset: Ties model metrics to business outcomes; balances innovation and delivery.
- Communication: Explains complex concepts to diverse stakeholdersexecs, product, and compliance. Ownership & Execution: Bias to action; ships PoCs fast and production features reliably
- What Youll Work On Build MCPs that standardize system integration, security control, and integrate with AI workflow/Agents.
- Deliver VibCoding & RAG: RAG-powered assistant with TypeScript SDK and Python inference service for Payment Network operators. Enhance the AI framework with reusable components: data connectors, evaluation harness, fallback/guardrails, prompt templates, and A/B testing tools
- Tech Stack Python: PyTorch, TensorFlow, FastMCP, FastAPI, Pandas TypeScript: Node.js, Express/Fastify, SDKs, tooling (tsup/esbuild) Infra: Docker, Kubernetes, Terraform, GitHub ActionsData & Retrieval: Airflow/Prefect, S3/GCS, Postgres, Redis, Weaviate/pgvector
Job Classification
Industry: BankingFunctional Area / Department: Engineering - Software & QARole Category: Software DevelopmentRole: Technical ArchitectEmployement Type: Full timeContact Details:
Company: MastercardLocation(s): Pune+ View Contact
Keyskills: software engineer kubernetes redis docker tensorflow model evaluation pytorch typescript graphql postgres architecture python github airflow ai llm pandas django compliance treasury kafka gitlab agile flask aws finance
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