Vetted Hibernate Professionals

“Candidate explicitly stated they do not have production agentic/LLM or generative AI experience, aside from spending a few hours becoming familiar with the process. Compensation expectation stated as 225,000.”

“Engineer working on high-throughput financial systems who uses AI pragmatically to accelerate development without sacrificing design ownership, correctness, or compliance. Particularly interesting for teams building regulated, real-time platforms: they have hands-on experience integrating fraud detection models into microservices, handling transaction ingestion, scoring, decisioning, and throughput-sensitive asynchronous workflows.”

“Full-stack engineer with experience at Vanguard, PNC, and Humana building customer-facing investment/banking flows and internal ops tools using Angular/React/TypeScript with Spring Boot microservices. Strong in shipping time-sensitive changes safely via automated testing/CI (JUnit/Mockito, Jenkins, SonarQube) and in operating event-driven microservices with Kafka (idempotency, retries, correlation IDs). Improved internal tool adoption by responding to ops/support feedback with query optimization and clearer search results.”

“Full-stack engineer with hands-on experience building a large-scale healthcare claims and provider-enrollment system end-to-end (React frontend, Spring Boot microservices, PostgreSQL on AWS). Optimized high-volume claims processing (millions of records/day) using indexing/pagination and asynchronous workloads via AWS Lambda/Kafka, and deployed containerized services with Docker/Jenkins on AWS.”

“Software engineer with experience at Walmart and Amex building customer-facing backend services and microservices at scale (RabbitMQ). Built an internal developer tooling platform integrating Figma with GitHub Copilot to automate consistent React component creation, adopted across multiple teams; emphasizes fast, safe iteration using metrics, feature flags, gradual rollouts, and automated testing.”

“Full-stack engineer with Bank of America experience modernizing a large-scale financial reporting platform. Built React frontends and Java/Spring Boot microservice APIs end-to-end, optimized data-heavy SQL performance (indexing/caching/pagination), and implemented an AI feature for forecasting and anomaly detection using Python/scikit-learn, with deployments supported on AWS.”

“Maintained and improved a set of JavaScript packages at JPMorgan, including a major refactor of an event-emission layer used in LLM streaming that delivered ~20% runtime speedup with no API changes. Known for a measurement-driven performance approach (profiling + simplification + validation), strong backward-compatibility discipline, and documentation that accelerates internal adoption and reduces support questions.”

“Cloud/Kubernetes-focused production engineer with experience running 99.95% uptime platforms across AWS/Azure/GCP. Strong in incident response and performance troubleshooting (including a 30% MTTR reduction), and in building secure CI/CD and Terraform-based IaC for AKS/GKE microservices with robust change controls and rollback practices. Notably does not have direct IBM Power/AIX/VIOS/HMC or PowerHA/HACMP ownership.”

SNEHA KUSUMA

Screened

Mid-level Java Full-Stack Developer specializing in banking and telecom platforms

Dallas, TX5y exp

“Frontend-focused engineer with experience at T-Mobile and U.S. Bank who maintained a TypeScript utility library (types, tests, build pipeline, and docs) adopted by multiple teams, and improved React workflow performance by refactoring components and optimizing data fetching. Known for pragmatic cross-team support—reproducing issues quickly, shipping well-tested fixes, and managing changes carefully to avoid breaking downstream apps.”

Harini Vinu

Screened

Intern Software Engineer specializing in cloud, big data, and test automation

New York, United States1y exp

“Internship experience at Qualitest building and deploying an LLM-powered test automation system that reduced manual test creation and improved efficiency (~40%). Demonstrates strong production engineering for LLM systems (timeouts/retries/monitoring/caching, prompt optimization, batching) and has scaled workflows to 100+ concurrent jobs; also has orchestration experience with AWS Step Functions and Kubernetes.”

Sanket Dumbare

Screened

Mid-Level Software Engineer specializing in cloud-native microservices and FinTech platforms

USA3y exp

“Backend/platform engineer who led an end-to-end Python (FastAPI) transaction analytics microservice for real-time financial monitoring, including SQS ingestion, scoring/aggregation, and low-latency APIs. Strong AWS + Kubernetes/GitOps background (EKS, ArgoCD, Jenkins, ECS/ECR, CloudWatch) with hands-on experience scaling event-driven systems and executing phased on-prem to AWS migrations.”

Deeresh Gajjala

Screened

Senior Software Engineer specializing in Java/Spring Boot microservices and AWS payments systems

Dallas, TX6y exp

“Senior software engineer with Amazon experience who owned end-to-end improvements to a real-time payment authorization service, rebuilding it as a reactive Spring WebFlux microservice with saga orchestration and Kafka event streaming, deployed on AWS EKS with strong observability. Also built React+TypeScript and Node/Express full-stack workflow apps (onboarding, campaign management, admin review) and has experience shipping quickly in ambiguous startup environments while maintaining reliability and data correctness.”

Sanket Mungikar

Screened

Mid-level Software Engineer specializing in backend systems and real-time analytics

California, USA5y exp

“Full-stack engineer at BigCommerce who combines customer-facing deployment ownership with hands-on AI/LLM systems work. Built and launched merchant analytics and predictive inventory workflows using React, TypeScript, FastAPI, Kafka, AWS, and RAG-style architectures, and has real production experience debugging non-deterministic AI issues caused by data pipeline freshness and event-ordering problems.”

“Candidate appears to work at the intersection of enterprise billing/payments systems and AI-powered support automation. They describe owning customer deployments, integrating PayPal/Stripe, building LLM/RAG workflows for finance operations, and handling production incidents affecting millions of invoice events with measurable improvements in resolution time and ticket volume.”

Ajay Desai

Screened

Mid-level Full-Stack Software Engineer specializing in FinTech and backend platforms

USA4y exp

“Built an AI-native legal research platform that automated analysis across 100,000+ dense legal documents, combining LLM workflows, async backend architecture, and conversational retrieval in production. Also brings cross-domain experience in investment-analysis agents and healthcare claims/billing systems, with a strong emphasis on reliability, deterministic orchestration, and safe handling of messy operational data.”

“Candidate indicated they live in New York but did not provide substantive details about their experience; they declined to discuss at least one topic as restricted and did not answer role-related questions with concrete examples.”

“Frontend engineer with hands-on experience leading architecture and quality practices across Angular and React/TypeScript products, including dynamic UI generation driven by backend configuration. Strong in building reusable design systems/component libraries and enforcing quality at scale via CI/CD SonarQube gates and comprehensive unit testing, with close collaboration alongside UX teams using Figma.”

“Backend/platform engineer who owned a real-time customer analytics microservice stack in Python/FastAPI with Kafka streaming into PostgreSQL, including schema enforcement (Avro) and high-throughput optimizations. Strong Kubernetes + GitOps practitioner (EKS/GKE, Helm, Argo CD) who has handled CI/CD reliability issues with automated pre-deploy checks and rollbacks, and supported major migrations (on-prem to AWS; VM to EKS) with blue-green cutover planning.”

“Full-stack developer who built an end-to-end Hotel Management System using React and Spring Boot with MongoDB and AWS. Has hands-on experience debugging API/data-fetching issues with Postman and validating results against the database, plus exposure to handling large data workloads with chunking and monitoring via Grafana/Tabula.”

“Full-stack engineer who has shipped and owned production analytics dashboards using Next.js App Router + TypeScript, combining server components for data-heavy pages with client components for interactive charts/filters. Also built a Temporal-orchestrated payment reconciliation workflow with versioning, idempotency, and exponential-backoff retries, and has hands-on Postgres query/index optimization using EXPLAIN ANALYZE.”

“LLM/agent engineer with production experience in the insurance claims domain, integrating OpenAI + LangChain into a claims platform to automate unstructured document extraction/classification and cut manual effort by 35%. Built reliable, fault-tolerant AWS/Kubernetes microservices with CloudWatch monitoring plus circuit breakers/retries/fallbacks, and implemented multi-step Spring Boot orchestration with schema validation, confidence gating, and human-in-the-loop handling for low-confidence cases.”

Ganesh Medepalli

Screened

Mid-level Java Developer specializing in Spring Boot microservices and AWS

USA3y exp

“Backend engineer with primary experience in Java/Spring Boot microservices, AWS (EC2/ECS/Lambda), and CI/CD automation with Jenkins. Supported modernization/migration efforts at Berkshire Hathaway and Citius Infotech by containerizing legacy components with Docker, refactoring services to be stateless, and managing infra changes via Terraform and Git-based workflows; has limited but practical Python API prototyping experience (Flask/FastAPI) and solid conceptual grounding in Kubernetes and Kafka.”

Raviteja Kambhampati

Screened

Mid-level Full-Stack Java Developer specializing in cloud-native microservices and React

San Francisco, CA5y exp

“Full-stack engineer who has owned customer-facing analytics and dashboard products end-to-end using TypeScript/React with Spring Boot microservices. Strong in scaling and stabilizing distributed systems (RabbitMQ, DLQs/retries, observability with correlation IDs) and in building internal tooling that consolidates ELK/CloudWatch signals to speed up support and operations; reported ~30% performance improvement on a recent dashboard.”