15+ years of software engineering experience [Java], including substantial hands-on development and technical leadership in Java-based enterprise applications.
Strong hands-on expertise in Java 21, with strong understanding of modern Java features and their application in enterprise-grade systems.
Strong experience with Java 21, Spring Boot 3.x, Spring Framework 6.x, Spring Security, Hibernate/JPA, and

RESTful APIs.

Hands-on knowledge of Virtual Threads, Records, Sealed Classes, Pattern Matching, enhanced Switch expressions, Streams, Collections, concurrency, JVM internals, memory management, garbage collection, and performance tuning.
Extensive experience designing and developing microservices-based, cloud-native, and distributed applications.
Strong Kubernetes experience covering deployments, services, ingress, configuration, secrets, autoscaling,

health probes, resource management, namespaces, RBAC, Helm, upgrade planning, and production troubleshooting.

Strong container engineering experience with Docker, secure base images, image scanning, registries, and container runtime practices.
Experience implementing and maintaining CI/CD pipelines and infrastructure automation using tools such as

GitHub Actions or Jenkins, Maven or Gradle, SonarQube, artifact repositories, Terraform or Bicep, and

Git-based workflows.

Hands-on experience with NoSQL databases, preferably MongoDB; experience with Azure Cosmos DB is also acceptable.
Practical experience with Microsoft Azure or equivalent cloud platforms, including cloud-native application deployment, monitoring, security, scalability, and resiliency.
Strong knowledge of automated testing using JUnit, Mockito, API testing tools, and frontend testing frameworks.
Experience with application security concepts, including authentication, authorization, OAuth 2.0, JWT, secure

API development, and vulnerability remediation.

Strong production support experience involving incident management, root-cause analysis, log analysis,

troubleshooting, performance optimization, defect resolution, and problem management.

Experience with monitoring and observability platforms such as Splunk, Dynatrace, Application Insights,

Grafana, or Prometheus.

Demonstrated experience working on application modernization, monolith-to-microservices transformation,

cloud migration, and legacy platform integration.

Experience participating in solution architecture discussions, technical design reviews, code reviews, release planning, and technology roadmap development.
Ability to translate business and functional requirements into scalable technical solutions, detailed designs, and implementation plans.
Strong experience in AI-Driven Software Development Lifecycle (AIDLC), utilizing enterprise-approved AI tools such as GitHub Copilot and Microsoft 365 Copilot to accelerate software development, testing, documentation,

troubleshooting, and delivery outcomes.

Experience working with business-critical applications, regulatory environments, security standards, and enterprise govern ance processes.

AI-Enabled Engineering Practices

Apply enterprise-approved AI-assisted engineering tools to coding, testing, documentation, code comprehension, and troubleshooting while complying with security and governance requirements.
Promote responsible adoption of AI-assisted development through human review, secure prompt and data handling, code-quality checks, traceability, and measurable engineering outcomes.

Azure and Kubernetes Engineering Expectations

Design secure AKS workloads with appropriate identity, network controls, secret management, pod security,

RBAC, autoscaling, resource limits, and workload isolation.

Implement Azure-native integration and monitoring patterns using services such as API Management, Key

Vault, Service Bus, Event Hubs, Azure Monitor, and Application Insights.

Troubleshoot container startup failures, readiness and liveness issues, image and registry problems, DNS and network connectivity, resource pressure, scaling behavior, and deployment rollback scenarios.
Apply infrastructure-as-code, immutable deployment practices, policy enforcement, vulnerability management,

and environment-promotion controls across the delivery lifecycle.

Roles & Responsibilities

Design, develop, and support scalable enterprise applications.
Develop and maintain microservices-based applications using Java, Spring Boot, and cloud-native technologies.
Collaborate with stakeholders to deliver business outcomes.
Own the end-to-end technical solution from requirements and architecture through development, testing,

deployment, stabilization, and post-production support.

Design and develop scalable Java and Spring Boot microservices, REST APIs, integration services, and event-driven components.
Define cloud-native architecture on Azure with emphasis on security, resilience, scalability, availability, cost awareness, and operational supportability.
Lead deployment and lifecycle management of applications on AKS or OpenShift using Docker, Kubernetes manifests, Helm charts, GitOps, and automated release pipelines.
Drive modernization of legacy and monolithic applications into modular, API-led, microservices-based, and cloud-native solutions.
Establish engineering standards for coding, API design, exception handling, logging, configuration, testing,

security, and observability.

Conduct architecture reviews, design reviews, code reviews, security reviews, performance reviews, and production-readiness assessments.
Implement resiliency patterns such as timeouts, retries, circuit breakers, bulkheads, rate limiting, graceful degradation, and disaster-recovery readiness.
Partner with product owners, architects, infrastructure, platform engineering, cybersecurity, database, QA, and business stakeholders to translate requirements into executable designs.
Lead technical troubleshooting for complex production issues and guide teams through root-cause analysis,

corrective actions, and preventive improvements

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