Java + AI

Ion Enterprise Solutions; Pune District; On-site; INR 4,000,000 - 7,000,000; Full time

Job summary

Mastercard seeks a Lead Software Engineer to design, build, and evolve cloud‑native platforms with high throughput and low latency. You will own solution design end‑to‑end, mentor engineers, and stay hands‑on with code, infrastructure, and automation across AWS, Kubernetes (EKS), Java microservices, and AI enablement.

You will lead architecture, build POCs, and drive engineering standards while delivering scalable cloud architectures and robust observability.

Qualifications

• 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, scalability, resiliency, and fault tolerance.

Responsibilities

• 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.
• Own non‑functional requirements (latency, throughput, availability, cost efficiency).
• 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.
• 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.
• Design and build solutions leveraging Agentic AI and Generative AI patterns.
• Apply tools such as GitHub Copilot 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.
• Design and maintain CI/CD pipelines; 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.

Skills

Java expertise

Distributed systems

High-throughput design

Low-latency optimization

Architectural judgment

Mentoring engineers

Code review

Tools

Kubernetes (EKS)

AWS

Spring Boot

gRPC / REST

AI tooling (Copilot)

Job description

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, 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.