Job Description
Job Requirements
Enterprise Architecture & Platform Leadership
Define and evolve reference architectures for distributed, lowlatency, highTPS systems deployed on AWS and Kubernetes (EKS).
Serve as a final technical escalation point for complex architectural and system design decisions across multiple teams.
Lead architectural tradeoff decisions spanning compute, networking, data, resiliency, observability, and cost—with explicit SLAs/SLOs.
Own and evangelize nonfunctional requirements (latency, throughput, availability, scalability, operability, security, cost efficiency).
Drive architectural consistency while enabling teamlevel autonomy through clear patterns and guardrails.
Deep HandsOn Engineering & Validation
Design and review critical execution paths in Javabased microservices (Spring Boot, gRPC, REST).
Build sophisticated POCs and spike solutions to derisk architecture decisions and emerging technologies before broad adoption.
Perform advanced production debugging across application, JVM, Kubernetes, and AWS layers.
Model prototypefirst engineering—validating ideas experimentally before standardization.
Remain handson enough that designs are grounded in real operational constraints.
Cloud & Kubernetes Expertise (AWS / EKS)
Architect And Guide Largescale AWS Environments Leveraging
EKS, EC2, ALB/NLB, VPC, IAM, Auto Scaling
Logging, metrics, distributed tracing, and alerting
Define Kubernetes Platform Patterns
Pod and node design
HPA and autoscaling strategies
MultiAZ and resilience models
Safe rollout, rollback, and canary strategies
Influence securityfirst, costaware, and operationally efficient cloud designs at scale.
Agentic AI & AIAugmented Engineering
Architect and prototype Agentic AI–driven engineering systems embedded into the SDLC.
Drive adoption and safe usage of GenAI tools such as GitHub Copilot and custom AI agents to:
Accelerate development and refactoring
Improve code quality, reviews, and test coverage
Reduce cognitive load for engineers
Experiment With AIenabled Workflows Across
Design Build Test Deploy Operate
Partner with governance and security stakeholders to ensure responsible, compliant AI usage.
Engineering Excellence, Standards & Mentorship
Define and evolve engineering standards, reference implementations, and best practices across the organization.
Perform deep architectural and code reviews for highimpact systems.
Mentor senior and staff engineers; coach teams on performance, cloudnative design, and system thinking.
Influence technical direction without authority through credibility, clarity, and results.
Work Experience
12+ years of handson software engineering experience
Expertlevel Java experience with largescale microservices platforms
Proven success designing and operating highthroughput, lowlatency systems
Advanced Knowledge Of
Distributed systems
Concurrency, performance tuning, and JVM internals
Fault tolerance, resiliency patterns, and graceful degradation
Cloud & Platform Engineering
Extensive production experience with Kubernetes (EKS) at scale
Deep expertise in AWS networking, security, and scaling patterns
Experience designing cloudnative, servicesbased or eventdriven platforms
Strong operational mindset (observability, incident response, reliability)
AI & Modern Engineering Practices
Handson experience applying Generative AI / Agentic AI in real engineering workflows
Active usage of GitHub Copilot or equivalent AI tooling
Experience integrating AI into developer platforms or SDLC automation (preferred)
Technical Leadership
Recognized ability to influence architecture across teams and platforms
Experience serving as a goto expert for the most complex technical problems
Strong communication skills—able to clearly articulate tradeoffs to engineers and leadership alike
Preferred Qualifications
Experience in payments, fintech, or largescale transaction processing systems
gRPC, async messaging, or streaming platforms (Kafka, etc.)
Strong observability and SREaligned practices
Proven track record modernizing legacy systems to cloudnative architectures
