Java + AI

We are seeking a Lead Software Engineer to design, build, and evolve highthroughput, lowlatency, cloudnative platforms at Mastercard. This role requires deep hands-on engineering expertise, strong architectural judgment, and the ability to prototype, experiment, and productionize modern solutions across AWS, Kubernetes (EKS), Java microservices, and Agentic AI.
You will operate as a technical ownerdriving solution design endtoend, mentoring engineers, and setting engineering standards while remaining deeply hands-on with code, infrastructure, and automation.

Key Responsibilities
Architecture & Solution Design

Lead the architecture and solutioning of distributed, lowlatency, highTPS systems running on AWS and EKS.
Design microservices-based Java platforms optimized for performance, resiliency, scalability, and operability.
Make architectural tradeoffs across compute, networking, data, and observability layers with measurable SLAs/SLOs.
Own non-functional requirements (latency, throughput, availability, cost efficiency).

Hands-on Engineering & Prototyping

Write production-grade Java code (Spring Boot / gRPC / REST) and review critical paths.
Build POCs, prototypes, and experiments to validate architecture choices and emerging technologies.
Troubleshoot complex production issues across application, platform, and cloud layers.
Lead by example through hands-on development, not just design reviews.

Cloud & Kubernetes (AWS / EKS)

Design and implement workloads on AWS, including:

EKS, EC2, ALB/NLB, IAM, VPC, Auto Scaling
Observability (logs, metrics, tracing)

Define Kubernetes-native patterns (HPA, pod design, multi-AZ resilience, rollout strategies).
Drive secure, scalable, and cost-aware cloud architecture.

Agentic AI & GenAI Enablement

Design and build solutions leveraging Agentic AI and Generative AI patterns.
Apply tools such as GitHub Copilot and custom AI agents to:

Improve developer productivity
Assist with code generation, refactoring, reviews, and testing

Experiment with AI-driven workflows across SDLC (design build test deploy).
Ensure responsible, secure, and governed use of AI in engineering systems.

CI/CD & Engineering Excellence

Design and maintain CI/CD pipelines supporting:

Automated builds, testing, security scans, and deployments
Infrastructure-as-Code and environment automation

Establish and enforce engineering standards, best practices, and quality guardrails.
Perform deep code and design reviews; mentor engineers on performance and cloud-native design.

Required Qualifications
Core Technical Skills

10+ years of hands-on software engineering experience
Strong Java expertise with microservices architectures
Proven experience building high-throughput, low-latency systems
Extensive AWS experience, including multiple production deployments on EKS
Deep understanding of:

Distributed systems
Concurrency, performance tuning, and scalability
Resiliency and fault tolerance

Cloud & Platform

Hands-on experience with Kubernetes (EKS) in production
Strong knowledge of AWS networking, security, and scaling patterns
Experience designing cloud-native, event-driven or service-based platforms

AI & Modern Engineering

Experience using Generative AI / Agentic AI in engineering workflows
Hands-on usage of GitHub Copilot or similar AI-assisted development tools
Experience integrating AI into developer tooling or platforms (preferred)

Engineering Leadership

Demonstrated ability to own architecture and execution
Experience mentoring engineers and influencing technical direction
Strong communication skills—able to explain complex technical decisions clearly

Preferred Qualifications

Experience in payments, fintech, or high-volume transaction systems
gRPC, async messaging, or streaming platforms experience
Observability and SRE-style practices
Experience modernizing legacy platforms to cloud-native architectures