Vetted Azure Kubernetes Service Professionals

Swetha Sai

Screened

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

Remote, USA4y exp

“JavaScript engineer with a track record of diagnosing and fixing real performance issues end-to-end—profiled a charting library freeze on large datasets, rewrote layout logic to batch updates, added tests, and got the PR merged upstream. Also has experience stabilizing backend services in ambiguous, fast-moving projects by defining priorities, tightening API contracts, and owning delivery through deployment.”

“Built a production, real-time clinical documentation system at HCA that converts doctor–patient conversations into structured clinical summaries using speech-to-text, LLM summarization, and RAG. Demonstrated measurable gains from medical-domain fine-tuning (clinical concept recall +18%, ROUGE-L 0.62 to 0.74) while meeting HIPAA constraints via PHI anonymization and encryption, and deployed via Docker/FastAPI with CI/CD and monitoring.”

“GenAI/ML engineer with hands-on experience building production financial intelligence and document summarization systems at Citibank. Stands out for combining LLM fine-tuning, hybrid RAG, multi-agent workflows, and strong MLOps/observability practices to deliver measurable business impact, including 60% faster analyst retrieval, 31% higher precision, and 99%+ uptime.”

“Junior developer with over a year of experience who is already applying AI-assisted engineering practices in production, including GitHub Copilot, ChatGPT, SonarQube, and OpenAI-based workflows. On a Citibank public portal built with .NET 8 and Angular, they used AI tooling plus CI/CD quality gates to speed delivery and reportedly reduce post-deployment bugs by 30-40% while maintaining strict security and compliance standards.”

“Software engineer/product-focused builder who delivered real-time supply chain inventory dashboards to replace a legacy system, integrating directly with ERP/WMS/TMS to eliminate manual reporting. Uses TypeScript/React with Redux Toolkit on the frontend and microservices + REST APIs on the backend, with performance improvements via Redis caching and a strong focus on user-feedback-driven prioritization and observability in distributed systems.”

“Frontend/platform-leaning engineer who owned a shared React component library (design-system style) adopted across multiple SPAs, with strong discipline around SemVer, deprecation strategy, and developer documentation. Also has backend/distributed-systems experience diagnosing and fixing a Kafka microservice race condition and has led prioritization/migration planning in an unstructured monolith-to-microservices environment (Centene).”

“Infrastructure engineer with hands-on ownership of a scaled IBM Power/AIX estate (AIX 7.x, VIOS, HMC; 2 frames/20+ LPARs) supporting critical middleware and database workloads, including live DLPAR changes and VIOS/SAN outage recovery. Also brings modern DevOps/IaC experience building GitHub Actions pipelines for Docker/Kubernetes deployments and provisioning AWS environments with Terraform (EKS/RDS/VPC/IAM) using modular, review-driven workflows.”

“Cloud/DevOps-focused engineer with production experience in Linux, AWS, Kubernetes, and cloud-native architectures. Has built GitHub Actions CI/CD pipelines for containerized Kubernetes deployments and implemented Terraform-based AWS infrastructure with modular design and remote state/locking (S3 + DynamoDB) plus PR/CI-driven change control.”

Sai Venkata Sathwik Golla

Screened

Mid-level Backend & Applied ML Engineer specializing in LLM systems and scalable APIs

Palo Alto, CA3y exp

“Backend engineer who significantly evolved an internal analytics/reporting platform (Python API + Postgres) powering self-service dashboards for product/business teams, focusing on reliability under heavy concurrent load and fast query performance. Demonstrates strong production engineering practices across API design (FastAPI), observability, incremental rollouts with feature flags, and data security using JWT/RBAC plus Postgres row-level security.”

“Backend engineer in airport operations who built a highly customizable BFF-based system connecting airport staff workflows to a baggage sortation engine. Their architecture cut per-airport customization from 100-150 engineering hours to 1-5 hours, improved long-running operation performance by 45%, and shipped in 4 months instead of 6. They also explored AI-assisted backend customization with human validation and test-based safeguards.”

Lawrence Prabhakar

Screened

Mid-level Full-Stack Java Developer specializing in FinTech

USA5y exp

“Engineer with a thoughtful, hands-on approach to AI-assisted software development, treating AI as a force multiplier for debugging, prototyping, and large-codebase work rather than a substitute for judgment. Particularly strong in multi-agent coding workflows, contract-driven development, and maintaining consistency across backend, frontend, and testing through shared schemas and OpenAPI-based coordination.”

“Full-stack engineer with experience spanning AI-powered product features and healthcare fraud detection systems. Has built end-to-end LLM-enabled applications, customer-facing recommendation systems at scale, and operational platforms that improved real-time investigations and flagged over 1,200 high-risk cases quarterly.”

Sai Naveen Reddy Reganti

Screened

Mid-level Full-Stack Engineer specializing in cloud-native FinTech and Healthcare systems

null4y exp

“Full-stack engineer working on customer-facing utility and banking platforms, with hands-on experience across React/React Native, Java/Spring Boot, Python/Django, AWS, and SQL performance tuning. Stands out for owning production systems end to end, improving CI/CD and deployment reliability, and delivering a measurable database optimization that cut CPU utilization from about 80% to 40%.”

“Built and deployed a production LLM-powered workflow assistant that automated internal marketing/production business tasks (document summarization, repeated Q&A, status updates). Demonstrates end-to-end applied LLM engineering: modular RAG architecture, hallucination/latency mitigation, automated evals to prevent prompt regressions, and Azure-based orchestration (Functions/Logic Apps) with monitoring and controlled rollouts.”

“Software engineer/product owner experience at UnitedHealth Group owning a high-volume claims eligibility console end-to-end (React/TypeScript + Spring Boot microservices) processing 1M+ transactions/day. Strong in event-driven architecture (Kafka/RabbitMQ), HIPAA-aligned security (OAuth/JWT/RBAC), and building internal observability tools that improve incident triage and production reliability.”

“ML/AI engineer with defense and commercial analytics experience: deployed a real-time aerial object detection system at Dynetics (YOLOv5 + TorchServe in Docker on AWS EC2) with drift-triggered retraining and 99.5% uptime, tackling ambiguous targets and weather degradation. Previously at Fractal Analytics, built and explained a churn prediction model for marketing stakeholders using SHAP and delivered it via a Flask API into dashboards, driving a reported 22% attrition reduction.”

“Backend/AI engineer who has built production Spring Boot APIs on AWS (JWT auth, Redis/MySQL) and solved a real-world silent data integrity issue by implementing idempotency keys plus DB constraints/transactions. Also shipped an LLM-based document Q&A feature using a RAG pipeline with evaluation + human review, and designed multi-step agent workflows with verification, retries, and escalation guardrails.”

“AI/LLM engineer who has shipped production RAG systems (including a 250K-document compliance knowledge tool on AWS) and focuses on reliability via citations, guardrails, and rigorous evaluation (Ragas/Opik/DeepEval). Also built a LangGraph-orchestrated webcrawler agent that cut research paper extraction from hours to minutes, and collaborated with clinical teams to deliver patient volume forecasting with an optimization layer for staffing.”

“Infrastructure/DevOps engineer with strong production ownership across AWS and Kubernetes, including leading real outage recoveries and building governance-heavy IaC/CI/CD in regulated environments. Has designed DR failover testing programs and implemented policy-as-code and peer-reviewed deployment gates to prevent repeat incidents; experience cited at Rackspace, Strategic Systems, and CTS.”

“Full-stack engineer with ~3.5 years of Java Spring Boot and React experience who built an end-to-end banking transaction platform using microservices, Kafka streaming, AWS RDS, and Dockerized CI/CD. Demonstrates strong performance and reliability engineering (async processing, DLQ/retries, idempotency, caching) plus secure cloud deployment practices; has also worked across banking, healthcare, and insurance domains.”

Mahesh Kota

Screened

Mid-level Full-Stack Java Developer specializing in cloud-native FinTech and Healthcare platforms

New York, NY5y exp

“Backend engineer with production experience building and scaling a Java/Spring Boot payment processing API on AWS (PostgreSQL/Redis) handling a few thousand RPS, including deep performance debugging (connection exhaustion) and observability (CloudWatch, Actuator, Zipkin). Also shipped application-layer AI features (OpenAI email summarizer with feedback loop, ~40% faster agent response times) and designed reliable multi-step workflow orchestration with retries and manual escalation, plus strong SQL tuning and Python engineering practices.”

“Software developer with hands-on experience refactoring a legacy .NET CMS into a newer API-driven application (ASP.NET MVC, JavaScript/HTML), including dynamic asset migration and resolving team merge conflicts in Bitbucket. Built automated tests with PyTest and used Postman for API validation, and leveraged Splunk for production issue detection; also worked on an end-to-end ticketing/workflow management project with prioritization and verification steps.”

“Analytics professional with Intuit experience spanning modern data stack work, behavioral segmentation, and applied AI. They built dbt/Snowflake pipelines powering retention and churn dashboards, automated feedback classification with OpenAI/LangChain, and partnered closely with product and marketing teams to turn analytics into onboarding, targeting, and lifecycle messaging decisions.”

Meet Vyas

Screened

Mid-level Software Engineer specializing in full-stack systems and AI applications

Tempe, AZ3y exp

“Software engineer with 3 years at Gap Inc. who led a major modernization from monolith/legacy frontend to a React and Spring Boot microservices architecture, delivering 25% cost savings, 30% faster releases, and 50% performance gains. Also built a 0→1 startup product, MealShare AI, using managed cloud services to rapidly launch a real-time food redistribution platform.”