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Hemanth - Backend Developer

[email protected]

Location: Arlington, Washington, USA

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HEMANTH REDDY Senior Java Backend Engineer | AI & Agentic Systems | Distributed Systems [email protected]| +1 (734) 821-5129 | linkedin.com/in/hemanth5636 | PROFESSIONAL SUMMARY Senior Java Backend Engineer with 8+ years of experience designing, developing, and deploying enterprise-scale distributed systems, cloud-native microservices, and AI-powered applications across E-Commerce, Banking, Financial Services, and Trading domains. Proven expertise across the full Software Development Life Cycle (SDLC) including requirements analysis, solution architecture, development, testing, deployment, monitoring, and production support in Agile/Scrum environments at Amazon, Fidelity, Salesforce, and JPMorgan Chase. Strong backend engineering background building scalable, resilient, high-throughput services using Java 8/11/17, Spring Boot, Spring Cloud, Spring MVC, Spring Security, Microservices, REST APIs, gRPC, and event-driven architectures. Deep experience decomposing legacy monoliths into distributed microservices and delivering secure, cloud-native platforms serving global production traffic. Hands-on experience building Generative AI and Agentic AI applications using Large Language Models (LLMs), Model Context Protocol (MCP), LangChain, LangGraph, Multi-Agent Orchestration, Retrieval-Augmented Generation (RAG), Prompt Engineering, Embeddings, Vector Search, and Semantic Search. Designed autonomous, DAG-based multi-tool orchestration layers with strict validation guards to eliminate LLM hallucinations and deliver deterministic, production-grade AI workflows. Extensive experience designing and operating cloud-native and containerized platforms on AWS and Google Cloud Platform (GCP) using Docker, Kubernetes, Custom Resource Definitions (CRDs), Operators, StatefulSets, Helm, GitOps, and CI/CD automation. Skilled in building secure applications with OAuth2, JWT, RBAC, IAM policies, and zero-trust security controls. Specialized in ultra-low-latency and high-performance systems engineering using Aeron Transport/Archive, Simple Binary Encoding (SBE), Staged Event-Driven Architecture (SEDA), lock-free ring buffers, off-heap memory management, and JVM tuning, delivering deterministic sub-millisecond latency profiles for mission-critical trading platforms. Experienced with high-throughput messaging and streaming (Apache Kafka, Kafka Streams, AWS SNS/SQS, Amazon Kinesis), relational and NoSQL databases (PostgreSQL, Oracle, MySQL, MongoDB, DynamoDB, Redis, Cloud Spanner), and observability tooling (Datadog, Grafana, Splunk, Prometheus, CloudWatch). Strong collaborator across product, architecture, and DevOps teams, mentoring engineers and driving engineering best practices. TECHNICAL SKILLS Programming Languages: Java (8/11/17), Golang, Python, Kotlin, JavaScript, TypeScript, SQL, Bash/Shell Backend & APIs: Spring Boot, Spring Cloud, Spring MVC, Spring Security, Microservices, REST APIs, gRPC, GraphQL, Event-Driven Architecture, WebSockets, JPA/Hibernate, Reusable Components Generative AI / LLMs / Agentic: Generative AI, Large Language Models (LLMs), Model Context Protocol (MCP), LangChain, LangGraph, Agentic AI, Multi-Agent Orchestration, DAG Execution Trees, Prompt Engineering, LLM Tool Routing, Context-Window Optimization, OpenAI, Azure OpenAI, Claude RAG / Search / NLP / ML: Retrieval-Augmented Generation (RAG), Embeddings, Vector Search, Semantic Search, Knowledge Retrieval, Document Intelligence, NLP, Text Classification, ML Inference APIs, Feature Engineering Messaging & Streaming: Apache Kafka, Kafka Streams, Schema Registry, AWS SNS/SQS, Amazon Kinesis, RabbitMQ, JMS Low-Latency & Performance: Aeron Transport & Archive, Simple Binary Encoding (SBE), SEDA, Agrona, Lock-Free Ring Buffers, Off-Heap Memory (DirectBuffer), FlatBuffers, UDP, JVM/GC Tuning Cloud Platforms: AWS (EKS, EC2, S3, RDS, Lambda, Kinesis, SNS/SQS, IAM, CloudWatch, Secrets Manager, ECR, CodeBuild), Google Cloud Platform (GKE, Cloud Spanner, Memorystore), Hyperforce Containers & DevOps: Docker, Kubernetes (CRDs, Operators, StatefulSets, Helm), GitOps, Jenkins, CI/CD Pipelines, PCF, Minikube, Infrastructure-as-Code Databases: PostgreSQL, Oracle, MySQL, MongoDB, DynamoDB, Redis (Memorystore), Cloud Spanner, JDBC, SQL, Query Optimization, Schema Design Testing & Quality: JUnit, Mockito, Integration Testing, End-to-End Testing, SonarQube, Cucumber, Gherkin, JMeter, BlazeMeter, Postman, Code Reviews Observability: Datadog, Grafana, Splunk, Prometheus, AWS CloudWatch, log4j, Distributed Tracing, SRE Practices Tools & Methodologies: Git, Gradle, Maven, Jira, Confluence, Agile/Scrum, SDLC, TDD, Sprint Planning, Backlog Grooming PROFESSIONAL EXPERIENCE Amazon Seattle, WA Dec 2024 Till Data Senior Software Engineer (SDE II) Java Backend + Agentic / Generative AI Designed and developed scalable Java 17 and Spring Boot microservices with Kafka-based event streaming to support high-volume supply-chain and fulfillment platforms serving global Amazon retail traffic across NA, EU, and FE regions. Architected a distributed, AI-driven operational assistant leveraging the Model Context Protocol (MCP) to bridge LLM orchestrators with multi-region telemetry, high-throughput supply-chain APIs, and asynchronous Kafka event streams. Built agentic AI workflows using LangGraph and LangChain to orchestrate multi-step, multi-agent reasoning, tool calling, function orchestration, and autonomous decision-making across FAS/GPI services. Designed a stateful multi-tool orchestration layer (Log Analyzer, Capacity Lookup, Payload Validator) that compiles natural-language prompts into deterministic, DAG-based backend execution trees, implementing strict validation guards to eliminate LLM hallucinations, cutting incident MTTH by 35% and redundant API calls by 25%. Implemented Retrieval-Augmented Generation (RAG) pipelines using vector embeddings, semantic search, chunking strategies, and enterprise knowledge repositories to ground LLM responses and improve operational decision support. Developed lightweight LLM workflows for log triage and runbook summarization across multi-region FAS/GPI services, significantly cutting mean time to first hypothesis on production incidents. Optimized context-window utilization via dynamic token-pruning and semantic chunking of system logs, ensuring long-context agent reasoning stayed within strict API token budgets while remaining highly performant. Optimized LLM command routing and execution-tree transformations via sub-graph caching and parallel tool execution using Java concurrency frameworks, reducing response-compilation latency by 40% to meet sub-second performance budgets at global fulfillment scale. Engineered an autonomous code-generation and refactoring agentic workflow that accelerated feature delivery across FAS/GPI services by automating the end-to-end development lifecycle. Delivered $1.1M in annual infrastructure cost savings through cache optimization, improving data serialization and storage efficiency and consolidating infrastructure by 224 Redis nodes across NA, EU, and FE regions. Architected end-to-end infrastructure for an FAS fleet, establishing foundational non-functional requirements (NFRs) and system reliability for a large-scale supply-chain platform. Led end-to-end design and cross-team review/approval for CandidateShipmentProcessor, a reusable component transforming order plans into optimized FlatBuffer payloads for low-latency downstream grouping and optimization; mentored an L4 engineer through implementation and delivery. Led migration from legacy to new service and SFCP-as-a-service migration for EU and FE regions, surfacing and quantifying legacy defects, driving cross-team alignment, and reducing false repromise noise by 30%. Containerized services with Docker, published images to Amazon ECR, and performance-tuned critical paths to sub-second latency at fulfillment scale. Implemented CI/CD pipelines with SonarQube quality gates, JUnit/Mockito unit tests, and integration tests to ensure production-grade reliability. Collaborated with product owners, architects, and cross-functional teams in an Agile/Scrum environment to translate business requirements into scalable AI-enabled backend services. Environment: Java 17, Spring Boot, Kafka, Model Context Protocol (MCP), LangChain, LangGraph, Generative AI, LLMs, RAG, Vector Search, Semantic Search, Agentic AI, Multi-Agent Orchestration, Prompt Engineering, Redis, FlatBuffers, Docker, Amazon ECR, AWS, SonarQube, JUnit, Mockito, CI/CD, Agile/Scrum. Fidelity Investments NJ, USA Oct 2023 Dec 2024 Software Engineer Java Backend + AI Migrated a legacy crypto-assets trading platform to a modernized public-cloud topology on AWS using Java, Aeron Transport, Aeron Archive, Simple Binary Encoding (SBE), UDP, Kafka, and PostgreSQL. Architected the core Market-Data-Feed-Handler using Staged Event-Driven Architecture (SEDA), pinning single-threaded Agrona agents to isolated CPU cores and using lock-free ring buffers to eliminate thread contention and context-switching. Eliminated JVM garbage-collection variance and allocation stalls along the critical trading path using off-heap memory (DirectBuffer) and pre-allocated object pools, ensuring flat, deterministic latency profiles under intense market volatility. Designed highly efficient binary message schemas using Simple Binary Encoding (SBE) to replace verbose text formats, optimizing CPU cache-line alignment and driving a 5x increase in message serialization throughput. Engineered a high-availability disaster-recovery mechanism using Aeron Archive and UDP topologies, automating deterministic replay of historical order books and market-data streams following component failover. Developed a reusable Feed-Handler Client SDK featuring customized binary headers with synchronized nanosecond timestamps to enforce distributed tracing and latency-budget telemetry across downstream consumers. Built Golang feed-handler client applications and internal tooling to interface with high-throughput market-data streams, leveraging Go's native concurrency for lightweight data processing. Designed and developed the Security-Master application for the crypto trading platform, ensuring high availability and secure persistence using AWS RDS (PostgreSQL) and AWS Secrets Manager. Built automated data pipelines using Amazon Kinesis to stream transactional logging and platform metrics downstream for real-time monitoring and analytics. Stood up local deterministic testing environments using Minikube and Docker container manifests, enabling developers to mirror and validate the full trading stack and the platform's security-master application. Collaborated with product owners and multiple teams to design, develop, and test features across applications while ensuring compliance with AWS IAM security policies. Environment: Java, Golang, Aeron Transport, Aeron Archive, SBE, SEDA, Agrona, Ring Buffers, UDP, Kafka, PostgreSQL, AWS (RDS, Kinesis, Secrets Manager, IAM, EC2), Docker, Minikube, Agile/Scrum. Salesforce Hyderabad, India Dec 2021 Aug 2022 Member of Technical Staff Go / Cloud Infrastructure Engineered custom Kubernetes CRDs and controllers in Go to orchestrate the lifecycle, auto-scaling, and dynamic configuration of core Salesforce applications migrating to public cloud infrastructure via Hyperforce. Developed and optimized Kubernetes Operators and controllers in Go using Docker and GitOps workflows to automate lifecycle management of complex cloud infrastructure. Architected and scale-tested foundational components of the FOX (Falcon Onboarding eXperience) platform, automating enforcement of complex Non-Functional Requirements (NFRs) and reducing public-cloud onboarding time by 40%. Built robust data-persistence and caching layers for internal cloud services using GCP Cloud Spanner and Memorystore (Redis), ensuring high availability and global consistency across clusters. Designed robust reconciliation loops and validation engines within AWS EKS to manage multi-tenant isolation, ensuring zero-downtime microservice provisioning with automated compliance and zero-trust security checks. Implemented declarative configuration modeling and GitOps pipelines to synchronize infrastructure states, engineering automated drift-detection mechanisms that reduced manual operational triage by 30%. Architected secure service communication and access controls within GKE clusters by implementing GCP IAM roles and service accounts, ensuring strict adherence to enterprise security compliance. Optimized container resource allocation and scheduling topologies via custom taints/affinities, profiling Hyperforce network boundaries to maintain sub-second internal routing latency under high load. Developed FOX application functionality using SFDB, Apex, Lightning Web Components (LWC), and JavaScript to capture Non-Functional Requirements and improve public-cloud onboarding velocity. Drove code quality and system reliability by implementing comprehensive unit, integration, and end-to-end test suites in Golang, delivering production-ready infrastructure code on schedule. Environment: Go, Kubernetes (GKE, EKS, CRDs, Operators, Controllers), Docker, GitOps, Hyperforce, GCP (Cloud Spanner, Memorystore/Redis, IAM), AWS EKS, Apex, Lightning Web Components (LWC), JavaScript, Agile/Scrum. JPMorgan Chase & Co. Hyderabad, India Aug 2017 Dec 2021 Associate Software Engineer Java Backend / Microservices Deconstructed a legacy monolithic system into a modern, scalable microservices architecture using Spring Cloud, Docker, and AWS Elastic Kubernetes Service (EKS), drastically improving fault tolerance and maintainability. Migrated enterprise Genesys applications from on-prem virtual machines to EKS clusters using Kubernetes StatefulSets to maintain application state while reducing infrastructure overhead cost by 40%. Developed an automated Spring Boot operator within the Kubernetes cluster to dynamically detect, register, and auto-configure newly deployed application instances. Designed and implemented an event-driven architecture leveraging Apache Kafka and AWS SNS/SQS, establishing decoupled, asynchronous communication boundaries across distributed microservices. Built and exposed secure RESTful APIs with Java and Spring Boot backed by Oracle, PostgreSQL, and MongoDB stores, with structured logging via log4j. Engineered high-availability data layers using MongoDB and Amazon DynamoDB, optimizing schema designs to support high-throughput, low-latency financial data querying. Streamlined release velocity by establishing robust CI/CD pipelines using Jenkins, AWS CodeBuild, Gradle, and Maven, minimizing human error and accelerating deployment frequency. Eliminated manual QA bottlenecks by developing end-to-end automated testing suites with Gherkin and Cucumber, integrating them into post-deployment CI/CD stages to ensure platform stability. Maintained high test quality through JUnit unit tests, Mockito mocking, and integration tests, with coverage and quality gates enforced via SonarQube. Performance-tuned Spring Boot and Kafka services to sub-second response under load, profiling hotspots and tuning thread pools, connection pools, and JVM settings. Authored Unix shell scripts to automate deployment, log rotation, and environment health checks across VM and containerized fleets. Maintained strong agile practices and knowledge sharing through sprint ceremonies, peer code reviews, and comprehensive technical documentation on Confluence to accelerate team onboarding. Environment: Java, Spring Boot, Spring Cloud, Apache Kafka, AWS (EKS, SNS, SQS, CodeBuild, DynamoDB), Docker, Kubernetes (StatefulSets, Helm), PCF, Eureka, Oracle, PostgreSQL, MongoDB, Jenkins, Gradle, Maven, JUnit, Mockito, SonarQube, Gherkin, Cucumber, log4j, Agile/Scrum. JPMorgan Chase & Co. Hyderabad, India Jun 2016 Jul 2017 Software Engineer Java Backend Developed a fa ade application abstracting on-prem Genesys services using Spring Boot and WebSockets for real-time data transfer between the fa ade and client applications. Maintained 95% code coverage with JUnit tests across all functionality and implemented a CI/CD pipeline to deploy the fa ade application to VMs. Built performance and load tests using JMeter and BlazeMeter to validate application throughput and stability under peak load. Developed a Vue.js application to monitor on-prem VM-deployed services in real time, improving operational visibility. Designed and consumed RESTful web services using JSON-based communication for integration between internal systems. Participated actively in Agile Scrum ceremonies including sprint planning, daily stand-ups, backlog grooming, and peer code reviews to ensure timely delivery. Environment: Java, Spring Boot, WebSockets, REST APIs, JSON, Vue.js, JUnit, JMeter, BlazeMeter, CI/CD, Git, Agile/Scrum. EDUCATION Master of Science, Information Systems University at Buffalo, NY, USA Aug 2022 May 2023 Bachelor of Engineering, Computer Science Osmania University, Hyderabad, India Jun 2013 May 2016 CERTIFICATIONS Certified Kubernetes Application Developer (CKAD) CNCF (2020) AWS Certified Solutions Architect Associate Amazon Web Services (2021) Docker Essentials Docker (2019) Keywords: continuous integration continuous deployment quality analyst artificial intelligence machine learning javascript sthree golang green card Colorado New Jersey New York Washington