Vetted Hibernate Professionals

“Built and shipped AI-powered workflow automation at Oracle, including an MCP-based agentic workflow with tool-calling and guardrails, plus Grafana monitoring and Confluence documentation. Also led a Django monolith-to-microservices migration at Chamsmobile using blue-green deployment and load balancer traffic splitting to avoid regressions while modernizing production systems.”

Aakanksha Desai

Screened

Junior Full-Stack Software Engineer specializing in React, Kubernetes, and AI-powered apps

Scottsdale, Arizona2y exp

“Backend/DevOps-leaning engineer managing multiple customer service platforms end-to-end (requirements through deployment). Built an in-house Python monitoring/alerting solution for Salesforce-to-Java contact sync jobs (Snowflake dependencies) that increased uptime ~60%, and helped modernize delivery by moving the team from manual releases to automated Jenkins-based deployments while coordinating an Oracle EBS→Fusion transition with business/data/IT stakeholders.”

Manasa Pippera

Screened

Senior .NET Full-Stack Developer specializing in cloud, IoT messaging, and real-time web apps

Franklin, TN6y exp

“Full-stack engineer who owns customer-facing web products end-to-end (React/TypeScript + Node.js), shipping frequent releases with strong testing, staged deploys, and production monitoring. Improved a key user flow by batching backend calls and simplifying frontend rendering, driving ~30% faster load times and ~30% higher completion rates. Also built an ops monitoring dashboard using ELK + Prometheus/Grafana that cut incident response time by 40% and has hands-on microservices messaging experience (RabbitMQ/Kafka, idempotency, DLQs).”

Prasad Krishna

Screened

Mid-level Full-Stack Developer specializing in healthcare analytics and microservices

Remote, USA4y exp

“Built and maintained an air-quality prediction backend in Python/Flask that serves offline-trained ML models to a React dashboard via JSON REST APIs. Demonstrates strong performance focus across the stack—low-latency inference under load, SQLAlchemy/Postgres query optimization, multi-tenant data isolation, and caching/background task strategies for high-throughput systems.”

Sumanth Gottipati

Screened

Mid-level Full-Stack Software Engineer specializing in cloud-native microservices and FinTech

New York, NY4y exp

“At Delta Airlines, built and shipped a production LLM-powered semantic search/troubleshooting assistant over maintenance logs and operational documentation using OpenAI embeddings and a vector database. Implemented hybrid ranking, query enrichment, and structured filters to improve relevance ~35% while optimizing latency via caching and vector tuning. Also designed a scalable Kafka + AWS (Lambda/SQS) ingestion pipeline with strong reliability/observability and an eval loop using real engineer queries and human review.”

Visaj Kapadia

Screened

Mid-Level Full-Stack Developer specializing in AWS and scalable web platforms

Santa Monica, CA5y exp

“Software engineer with hands-on AWS experience optimizing an email campaign delivery system—re-architected a monolithic worker into multi-threaded/multi-worker ECS components to boost throughput ~600% (5 to 35 emails/sec). Comfortable debugging production issues (e.g., SQS/EventBridge policy misconfiguration) and emphasizes maintainable delivery via design docs, TDD, versioned APIs, and strong test coverage.”

Rambabu Dhanavath

Screened

Mid-level Software Engineer specializing in backend and cloud-native microservices

United States5y exp

“Backend/cloud engineer with 5 years of experience who has shipped a production internal ops LLM assistant end-to-end using Spring Boot microservices on AWS. Stands out for designing controlled, safety-first agent orchestration with deterministic tool access, Redis/DB-backed recoverable state, and strong observability/evaluation practices to improve reliability in production.”

Nidhip Patel

Screened

Mid-level Software Engineer specializing in AI/ML and full-stack development

United States3y exp

“Backend Java engineer with strong platform/DevOps experience: modernized an insurance claims legacy monolith into DDD-aligned microservices, deployed containerized services on Kubernetes with Jenkins CI/CD and static analysis gates, and implemented GitOps using ArgoCD. Also led major AWS migration planning with dependency mapping and network monitoring to uncover hidden dependencies, and built Kafka-based real-time event streaming with schema-registry-driven evolution.”

“Full-stack Java developer from Cognizant who built a real-time transaction monitoring and tracking platform for operations and customer visibility. Stands out for combining Spring Boot, React/TypeScript, Kafka, and CI/CD tooling to ship near real-time dashboards, while also working directly with users to refine requirements and improve performance in high-volume transaction environments.”

Dinesh Guguloth

Screened

Mid-level Software Engineer specializing in full-stack cloud-native applications

New York, NY4y exp

“Full-stack engineer with cloud and GenAI experience who has owned production features end-to-end, including a reporting dashboard optimized from 14s to 5s using query/API refactoring and monitored via AWS CloudWatch. Also productionized an OpenAI-powered chatbot using LangChain with prompt design, guardrails, and evaluation via production logs and user feedback, and has led incremental legacy-to-microservices modernization with parallel run to avoid regressions.”

“Full-stack Java developer (~4 years) who built a telecom asset management system end-to-end with React and Spring Boot, and led/participated heavily in migrating it from a monolith to Spring Cloud-based microservices. Experienced with high-volume, data-driven workloads using Kafka (partitioning, batching, resilient consumers) and production observability via centralized logging with ELK and Splunk.”

“Full-stack engineer with strong React/TypeScript and Java Spring Boot microservices experience who has built end-to-end task management and real-time, data-intensive dashboards. Demonstrates practical depth in security (JWT, RBAC, token refresh), performance optimization (indexing/aggregations, virtualization, caching), and cloud deployment (AWS, Docker, Jenkins, Kubernetes).”

“Backend engineer with cloud-native Python/Flask experience building high-throughput financial platforms (loan origination intelligent document processing and real-time fraud detection). Has scaled microservices on AKS with event-driven Azure messaging, delivered measurable performance gains (e.g., 700ms→180ms query latency; ~40% API improvements), and implemented strong security controls (OAuth2/JWT, Azure AD RBAC, audit logging, AES-256/TLS) for sensitive regulated data.”

“Backend/full-stack Java engineer at PNC Bank specializing in real-time fraud detection systems. Built event-driven Spring Boot + Kafka microservices with PostgreSQL/Redis performance tuning, and shipped a production LLM-powered RAG feature for fraud analysts with strong guardrails (grounded internal data, structured prompts with references, human-in-the-loop) plus an evaluation loop using labeled historical fraud cases.”

Filmon Tesfay

Screened

Senior Full-Stack Developer specializing in cloud-native FinTech and AI platforms

New York, NY8y exp

“Full-stack engineer with strong production ownership: built and operated a real-time transaction monitoring/fraud-alerting system using Java Spring Boot, Kafka, Docker, and AWS with CI/CD. Demonstrates metrics-driven operations (latency, stability, consumer lag, true/false positives) and reliability patterns for integrations (idempotency, retries/backoff, DLQs, reconciliation/backfills), plus modern React/TypeScript + Node/Postgres architecture experience.”

Nicholas Huang

Screened

Mid-level Full-Stack Developer specializing in FinTech web applications

Cincinnati, OH6y exp

“Front-end engineer experienced modernizing legacy React/TypeScript applications, including building a highly customized navigation system controlled by feature flags and documenting it for cross-team adoption. Demonstrates strong performance optimization skills (profiling, provider refactors, memoization) and deep debugging ability, including resolving UI jank traced to Reach Router’s accessibility-driven focus behavior.”

Chandana Arikacherla Nagendran

Screened

Mid-level Full-Stack Developer specializing in Java, Spring Boot, and Angular

Columbus, Ohio4y exp

“Full-stack engineer who modernized mission-critical legacy COBOL/AS400 systems into a Java + Angular/TypeScript web application, owning backend APIs, UI, database performance tuning, and JWT security end-to-end. Built and transitioned an internal docketing/hearing scheduling system with complex business rules, emphasizing smooth adoption, performance, and quality through phased agile delivery.”

Valeriy Filin

Screened

Senior Backend/Cloud Engineer specializing in IaC, SaaS platforms, and ML/Computer Vision

Aliso Viejo, CA19y exp

“Backend/infrastructure engineer with experience across API development (FastAPI/MySQL/SQLAlchemy), Kubernetes deployments, and large-scale data processing—built a Dockerized Python pipeline to pre-aggregate ~1B Graylog events for efficient querying. Has enterprise infrastructure automation background at Hewlett Packard Enterprise (Datafabric) using Terraform/Ansible with fail-fast and rollback practices, plus Kafka-based sensor streaming prototypes to Google Cloud with Java workers and autoscaling.”

Rahul Solleti

Screened

Mid-Level Software Engineer specializing in cloud-native microservices and full-stack web apps

United States5y exp

“Backend/platform engineer focused on real-time financial fraud detection and transaction monitoring, building low-latency FastAPI + Kafka systems with strong reliability patterns (DLQs, idempotency) and cloud observability. Has hands-on Kubernetes delivery across AWS EKS and Azure AKS with automated CI/CD and GitOps-style deployments, plus experience migrating legacy C# / Java monoliths to containerized microservices using Terraform/ARM and zero-downtime rollout strategies.”

Sanjana Akula

Screened

Senior Full-Stack Software Engineer specializing in cloud-native microservices and FinTech

New York, NY5y exp

“Front-end engineer with experience at Optum and Wells Fargo maintaining internal React/Angular component libraries and design-system-aligned UI modules used across multiple apps. Known for stabilizing shared libraries via semantic versioning, Jest test automation, and high-quality documentation, plus measurable performance wins (≈40% faster dashboard loads) through profiling-driven React and API optimizations.”

Shital Agarwal

Screened

Senior Software Engineer specializing in backend, microservices, and full-stack web development

New Jersey, USA5y exp

“Software engineer who delivered a dynamic service-fee system for a Belgian online grocery e-commerce platform by carving out a Spring Boot microservice from a monolith, integrating Google distance APIs, Redis caching, and CI/CD for production rollout. Also built an OpenAI-powered university chatbot with agent/workflow orchestration during academia, emphasizing availability and fallback behavior.”

“Backend-focused engineer with banking-domain deployment experience who has owned releases end-to-end, from discovery and API/database implementation through post-launch stabilization. Brings a reliability-first mindset across distributed systems, incident response, and messy real-world data handling, and has also applied that foundation to retrieval-based LLM workflows in production-oriented cloud environments.”

“Full-stack/backend-leaning engineer with hands-on experience building transaction-processing systems using React, TypeScript, Node.js, MySQL, and Spring Boot microservices. They have owned services in production on AWS EKS, diagnosed peak-traffic failures via CloudWatch, and driven architectural modernization to Kafka-based microservices that improved scalability, deployment speed, and reliability.”

“Software engineer who has shipped both core web platform features (secure user authentication/profile management) and production LLM systems. Built an internal documentation knowledge assistant using a full RAG pipeline (OpenAI embeddings, vector DB, semantic search, reranking) with evaluation loops and a scalable document-ingestion pipeline for PDFs/FAQs, iterating based on metrics and user feedback.”