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Vetted Microservices Professionals
Pre-screened and vetted.
Senior Full-Stack Developer specializing in Java microservices and AWS cloud
Mid-level Python Backend Engineer specializing in cloud-native microservices and event-driven systems
Senior DevOps/Cloud Engineer specializing in AWS, Kubernetes (EKS), Terraform, and DevSecOps
Senior AI/ML Engineer specializing in MLOps and Generative AI (LLMs/RAG)
Mid-level DevOps Engineer specializing in cloud infrastructure, automation, and CI/CD
Mid-level Java Full-Stack Developer specializing in cloud-native microservices
Engineering Leader specializing in FinTech, payments, and enterprise platforms
Mid-level Cloud Security & DevSecOps Engineer specializing in AWS/Azure security automation
Mid-Level .NET Full-Stack Developer specializing in Azure cloud and SPA development
Mid-Level Full-Stack Java Developer specializing in Spring Boot microservices and Angular
Mid-level Backend Software Engineer specializing in Java, Spring Boot, and AWS
Director of Information Security and Security Engineer specializing in cloud compliance
Director-level Engineering Manager/Architect specializing in enterprise SaaS and cloud platforms
Bharath Reddy Nallu
Mid-level Machine Learning Engineer specializing in NLP and scalable MLOps
“Data/ML engineer in financial services (Northern Trust) who built a production RAG-based LLM system to connect structured transaction/portfolio data with unstructured market and internal documents for risk teams. Strong in end-to-end pipelines (AWS Glue/Airflow/PySpark), entity resolution, and taking models from prototype to reliable daily production with performance tuning (LoRA + TensorRT) and monitoring.”
Bhuvaneswari Kudaravalli
Mid-Level Full-Stack Software Engineer specializing in TypeScript, React/Next.js, and Node/Nest APIs
“Full-stack engineer who built and scaled an AI-powered web product (React/Next.js + TypeScript/NestJS) with MongoDB, Redis, and RabbitMQ. Strong in rapid iteration while maintaining production quality—uses versioned APIs, feature flags, CI/CD, and observability (correlation IDs/structured logs) to ship frequently and debug distributed workflows. Also created an internal operations dashboard for real-time visibility and control of background jobs/AI workflows that was adopted quickly by ops and product teams.”
Bhavesh Ittadwar
Senior Full-Stack Engineer specializing in scalable web and cloud systems
“JavaScript engineer who built a Michelin-specific headless CMS forms platform based on apostrophe-forms, powering forms across 400+ Michelin websites. Designed an extensible, SOLID-aligned modular field architecture with a shared design system, cutting hundreds of lines of per-project code across 10+ implementations while driving cross-device compatibility and performance (BrowserStack, Lighthouse, SSR).”
Praniket Ketan Walavalkar
Junior AI Software Engineer specializing in RAG agents and cloud data platforms
“AI Software Engineer (student employee) at University of Washington IT who helped deploy "Purple," a governed, explainable LLM platform on Azure used by 100,000+ students/faculty/staff. Independently led scalable reliability efforts by building automated agent quality/load/red-team testing and CI/CD health validation (Playwright/Node.js, Azure DevOps), and previously built an explainable AI scheduling assistant for clinical operations at Proliance Surgeons.”
Sudheer koki
Mid-level AI/ML Engineer specializing in predictive modeling, data pipelines, and RAG systems
“Built and productionized an LLM-powered internal knowledge search system in a regulated environment, using embeddings/vector DB retrieval with strict grounding and confidence gating to reduce hallucinations. Reported ~45% accuracy improvement over keyword search and implemented end-to-end orchestration, monitoring, CI/CD, and incremental re-indexing to manage latency and data freshness while driving adoption with business stakeholders.”