Job Description
We are seeking a Senior Java Backend Engineer to design, build, and evolve high-throughput, cloud-native backend systems that power mission-critical Systems of Engagement (SoE). This role requires deep expertise in Java and Spring Boot, distributed processing, DevOps automation, and system observability, along with experience modernizing legacy platforms to Azure and AWS.
The ideal candidate brings strong engineering judgment, a performance-first mindset, and recent hands-on experience integrating LLM-based and agentic AI capabilities into enterprise platforms.
Key Responsibilities
Backend & SoE Architecture
Design and implement high-throughput SoE layers using Java and Spring Boot
Build scalable, fault-tolerant services supporting real-time and near-real-time user interactions
Apply best practices for API design, service orchestration, and resiliency patterns
Distributed & Batch Processing
Develop and maintain distributed batch and asynchronous processing workflows
Ensure reliable data movement, consistency, and fault recovery across systems
Optimize throughput and latency for large-scale processing workloads
Cloud-Native Development
Build and deploy cloud-native services on GCP or AWS
Leverage managed cloud services to improve scalability, reliability, and cost efficiency
Support legacy-to-cloud migrations, ensuring data integrity and minimal disruption
DevOps, CI/CD & Automation
Design and maintain automated CI/CD pipelines for build, test, and deployment
Apply Infrastructure-as-Code and DevOps best practices
Enable frequent, safe releases through automation and strong quality gates
Observability & Performance Optimization
Implement robust monitoring, logging, and alerting using Splunk, New Relic, or similar tools
Diagnose and resolve performance bottlenecks and production issues
Continuously improve system reliability, availability, and operational excellence
AI & Advanced Capabilities
Integrate LLM-based and agentic AI capabilities into backend services and workflows
Collaborate with data science and platform teams to operationalize AI models
Ensure AI-enabled services meet enterprise standards for security, scalability, and governance
Collaboration & Technical Leadership
Participate in architecture and design reviews
Mentor junior engineers and promote engineering best practices
Collaborate with product, platform, security, and data teams to deliver end-to-end solutions
Required Qualifications
10+ Years Strong expertise in Java and Spring Boot
Proven experience designing high-throughput backend systems and SoE layers
Hands-on experience with cloud-native development on GCP or AWS
Experience with distributed processing and batch systems
Strong background in CI/CD automation and DevOps practices
Experience with monitoring and observability tools (Splunk, New Relic, or similar)
Demonstrated success in legacy-to-cloud migration efforts with a focus on data integrity
Preferred / Nice-to-Have Skills
Experience with messaging and streaming platforms (Kafka, RabbitMQ, etc.)
Familiarity with containerization and orchestration (Docker, Kubernetes)
Exposure to service mesh and API management platforms
Experience implementing AI/ML or LLM-enabled features in production systems
Cloud certifications in GCP or AWS
What Success Looks Like in This Role
Highly reliable, scalable backend services powering critical user interactions
Measurable improvements in system performance, observability, and deployment velocity
Smooth legacy-to-cloud transitions with strong data consistency and reliability
Practical, production-grade integration of AI capabilities delivering real business value
Job Requirements
We are seeking a Senior Java Backend Engineer to design, build, and evolve high-throughput, cloud-native backend systems that power mission-critical Systems of Engagement (SoE). This role requires deep expertise in Java and Spring Boot, distributed processing, DevOps automation, and system observability, along with experience modernizing legacy platforms to Azure and AWS.
The ideal candidate brings strong engineering judgment, a performance-first mindset, and recent hands-on experience integrating LLM-based and agentic AI capabilities into enterprise platforms.
Key Responsibilities
Backend & SoE Architecture
Design and implement high-throughput SoE layers using Java and Spring Boot
Build scalable, fault-tolerant services supporting real-time and near-real-time user interactions
Apply best practices for API design, service orchestration, and resiliency patterns
Distributed & Batch Processing
Develop and maintain distributed batch and asynchronous processing workflows
Ensure reliable data movement, consistency, and fault recovery across systems
Optimize throughput and latency for large-scale processing workloads
Cloud-Native Development
Build and deploy cloud-native services on GCP or AWS
Leverage managed cloud services to improve scalability, reliability, and cost efficiency
Support legacy-to-cloud migrations, ensuring data integrity and minimal disruption
DevOps, CI/CD & Automation
Design and maintain automated CI/CD pipelines for build, test, and deployment
Apply Infrastructure-as-Code and DevOps best practices
Enable frequent, safe releases through automation and strong quality gates
Observability & Performance Optimization
Implement robust monitoring, logging, and alerting using Splunk, New Relic, or similar tools
Diagnose and resolve performance bottlenecks and production issues
Continuously improve system reliability, availability, and operational excellence
AI & Advanced Capabilities
Integrate LLM-based and agentic AI capabilities into backend services and workflows
Collaborate with data science and platform teams to operationalize AI models
Ensure AI-enabled services meet enterprise standards for security, scalability, and governance
Collaboration & Technical Leadership
Participate in architecture and design reviews
Mentor junior engineers and promote engineering best practices
Collaborate with product, platform, security, and data teams to deliver end-to-end solutions
Required Qualifications
10+ Years Strong expertise in Java and Spring Boot
Proven experience designing high-throughput backend systems and SoE layers
Hands-on experience with cloud-native development on GCP or AWS
Experience with distributed processing and batch systems
Strong background in CI/CD automation and DevOps practices
Experience with monitoring and observability tools (Splunk, New Relic, or similar)
Demonstrated success in legacy-to-cloud migration efforts with a focus on data integrity
Preferred / Nice-to-Have Skills
Experience with messaging and streaming platforms (Kafka, RabbitMQ, etc.)
Familiarity with containerization and orchestration (Docker, Kubernetes)
Exposure to service mesh and API management platforms
Experience implementing AI/ML or LLM-enabled features in production systems
Cloud certifications in GCP or AWS
What Success Looks Like in This Role
Highly reliable, scalable backend services powering critical user interactions
Measurable improvements in system performance, observability, and deployment velocity
Smooth legacy-to-cloud transitions with strong data consistency and reliability
Practical, production-grade integration of AI capabilities delivering real business value