Description
Our Purpose
Mastercard powers economies and empowers people in 200+ countries and territories worldwide. Together with our customers, we're helping build a sustainable economy where everyone can prosper. We support a wide range of digital payments choices, making transactions secure, simple, smart and accessible. Our technology and innovation, partnerships and networks combine to deliver a unique set of products and services that help people, businesses and governments realize their greatest potential.
Title and Summary
Senior AI Engineer (AI enablement for data platform) Who is Mastercard?Mastercard is a global technology company in the payments industry. Our mission is to connect and power an inclusive, digital economy that benefits everyone, everywhere by making transactions safe, simple, smart, and accessible. Using secure data and networks, partnerships and passion, our innovations and solutions help individuals, financial institutions, governments, and businesses realize their greatest potential.
Our decency quotient, or DQ, drives our culture and everything we do inside and outside of our company. With connections across more than 210 countries and territories, we are building a sustainable world that unlocks priceless possibilities for all.
Overview
The Enterprise Data Solutions team is looking for experienced AI Engineer to design and implement AI capabilities within our enterprise Data Platform, which powers multiple application teams. The platform includes NiFi, Airflow, Spark, Kubernetes, MinIO, and Ceph, and your mission is to make AI a first-class citizen in this ecosystem.
Job Title: Senior AI Engineer – Data Platform Engineering
Location: Pune, India
About the Role
As a Senior AI Engineer, you will build AI services, APIs, and reusable components that enable application teams to easily integrate ML/GenAI into their workflows—such as intelligent data processing, anomaly detection, semantic search, and RAG (Retrieval-Augmented Generation). This is a platform engineering role with AI specialization, requiring strong technical depth and a product mindset.
Key Responsibilities
Embed AI into the platform:
Develop AI microservices and APIs deployable on Kubernetes for inference, embeddings, and data enrichment.
Create NiFi processors and Airflow operators for AI tasks (e.g., NLP extraction, PII detection, summarization).
Build Spark-based AI pipelines for batch and streaming workloads.
Reusable AI capabilities:
Implement RAG services integrated with MinIO/Ceph for enterprise data search.
Provide pre-built AI components (e.g., anomaly detection, classification) for application teams.
Platform integration & MLOps:
Design model lifecycle management (registry, versioning, retraining) within the platform.
Enable observability for AI services (metrics, drift detection, performance dashboards).
Security & Governance:
Apply guardrails for GenAI (content filtering, prompt safety).
Ensure compliance with enterprise standards (data privacy, encryption, IAM).
Collaboration:
Work with platform engineers to integrate AI seamlessly.
Document APIs, usage patterns, and best practices for application teams.
Technical Skills
7+ years in AI/ML engineering; 3+ years in production systems.
Strong Python (ML stack: scikit-learn, PyTorch/TensorFlow).
Hands-on with NiFi, Airflow, Spark, and Kubernetes.
Experience with object storage (MinIO/Ceph) and S3 APIs.
Knowledge of MLOps (MLflow, CI/CD, containerization).
Familiarity with vector search (FAISS/HNSW) and embeddings.
Soft Skills
Strong problem-solving and analytical skills.
Effective communication and collaboration across teams.
Ability to work independently and take ownership of deliverables.
Willingness to mentor junior engineers and contribute to team growth.
Qualifications
Bachelor's degree in computer science, Engineering, or a related field.
7+ years of experience in software engineering, preferably in data platform or infrastructure teams.
Prior experience in enterprise environments or large-scale systems is preferred.
Corporate Security Responsibility
All activities involving access to Mastercard assets, information, and networks comes with an inherent risk to the organization and, therefore, it is expected that every person working for, or on behalf of, Mastercard is responsible for information security and must:
Abide by Mastercard's security policies and practices;
Ensure the confidentiality and integrity of the information being accessed;
Report any suspected information security violation or breach, and
Complete all periodic mandatory security trainings in accordance with Mastercard's guidelines.
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