Ankit Yadav
SOFTWARE ENGINEER | JAVA BACKEND ENGINEER | CLOUD-NATIVE MICROSERVICES
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About
Software Engineer with 4+ years of experience designing and building scalable, cloud-native enterprise applications using Java 21, Spring Boot, Microservices, Kafka, Kubernetes, Docker, and AWS. Proven expertise in developing high-performance distributed systems, RESTful APIs, event-driven architectures, and secure backend services supporting millions of transactions. Experienced in CI/CD automation, cloud infrastructure, AI/LLM integrations, and full-stack development using React and TypeScript.
Strong understanding of software design principles, system scalability, performance optimization, observability, and production support within Agile environments
Experience
Software Engineer at ThredUp (2025-04 – Present)
- Designed and developed scalable Java 21 microservices using Spring Boot, Spring WebFlux, and Domain-Driven Design (DDD), improving developer onboarding productivity by 35% and reducing environment setup time from days to minutes.
- Built high-throughput event-driven architectures using Apache Kafka, Kafka Streams, and Apache Flink, processing billions of real-time events while improving platform throughput by 45% with sub-100ms latency.
- Optimized JVM performance, Kafka consumers, and Kubernetes autoscaling strategies, reducing p99 latency by 40% and lowering cloud infrastructure costs by 25%.
- Developed secure backend services using Spring Security, OAuth2, JWT, REST APIs, GraphQL, and gRPC for enterprise-scale internal platforms.
- Designed cloud-native applications on AWS using Docker, Kubernetes (EKS), Helm, and ArgoCD, enabling highly available, zero-downtime deployments through automated CI/CD pipelines.
- Integrated AI-powered platform services using LLM orchestration APIs, RAG workflows, prompt validation, model routing, and safety guardrails to support intelligent enterprise applications.
- Built scalable media processing services for file upload, validation, asynchronous processing, transcoding, object storage (Amazon S3/GCS), and CDN delivery.
- Developed payment and subscription management services using PostgreSQL, Redis, and idempotent APIs supporting billing, reconciliation, and transaction processing.
- Collaborated with cross-functional engineering teams to deliver production-ready features following Agile methodologies, code reviews, unit testing, and software engineering best practices.
- Built internal dashboards using React, TypeScript, Next.js, and GraphQL to improve platform observability, operational monitoring, and engineering productivity.
Software Engineer at Apple (2020-11 – 2023-08)
- Developed scalable backend applications using Java, Spring Boot, and Spring MVC for AI-assisted legacy application modernization and enterprise software transformation.
- Built orchestration services that improved COBOL-to-Java translation accuracy by 40%, significantly reducing manual verification efforts and accelerating modernization initiatives.
- Designed automated validation frameworks using JUnit, Mockito, and custom testing utilities, reducing manual code review effort by 38% while improving software reliability.
- Engineered asynchronous job scheduling and queue-based processing solutions, increasing batch processing efficiency by 35% across distributed enterprise workloads.
- Developed secure RESTful APIs for job orchestration, metadata management, validation pipelines, and distributed processing systems.
- Designed and implemented scalable microservices architecture, improving modularity, maintainability, and deployment efficiency across enterprise applications.
- Built responsive engineering dashboards using React, HTML5, CSS3, and REST APIs for monitoring translation pipelines and validation results.
- Optimized data access layers using Hibernate, JPA, and SQL performance tuning techniques, improving query performance across large-scale metadata repositories.
- Deployed containerized applications using Docker, Kubernetes, and IBM Cloud, enabling consistent deployments across development, testing, and production environments.
Education
Master of Science in Computer Science – University of California, Riverside (2023 – 2025)

