Vetted Kubernetes Professionals

Punith Jayaramu

Screened

Mid-Level Full-Stack Software Engineer specializing in FinTech and Mortgage systems

Auburn Hills, MI3y exp

“Full-stack engineer with deep AWS serverless and reliability experience in fintech/underwriting systems, including eligibility scoring and dynamic rule deployments. Built and productionized an LLM-powered incident RCA assistant (Bedrock Claude 3 + custom RAG + React) achieving 92% precision and ~75% MTTR reduction, with mature guardrails (evals, drift monitoring, HITL, audit logs) and strong operational rigor (canaries, chaos testing, DLQ remediation).”

Sree Gautham Alluri

Screened

Mid-level Robotics & AI Developer specializing in autonomous navigation and LLM-powered robotic systems

Exton, PA6y exp

“Robotics Support Engineer at HAI Robotics supporting a 385-robot warehouse fleet at a Shein client site. Built a production automation and reporting workflow to diagnose and resolve abnormal shelf locations, cutting incidents from ~250/day to ~25/day while providing actionable root-cause data to client/ops/maintenance. Hands-on ROS 2 (Humble) debugging across Nav2/localization/TF and sensor integration issues including QoS and firmware coordination.”

Sridhar Duggireddy

Screened

Executive Technology Leader specializing in Cloud Platforms, DevOps, and AI/ML

Tampa, FL21y exp

“Early-stage startup CTO helping build an AI-powered parenting assistant app with features spanning advice, shopping, task management, and inventory management. The team is currently testing an MVP with their network while the candidate simultaneously learns the seed/Series fundraising process through Connectd and early investor conversations.”

Sivamalai Chandrasekar

Screened

Mid-level Forward Deploy Engineer specializing in cloud platforms and customer deployments

Aspen, CO4y exp

“Built and deployed VotingConnect end-to-end, owning everything from stakeholder discovery to architecture, full-stack implementation, and post-launch stabilization, with reported outcomes including 99.9% uptime and a 40% increase in voter participation. Currently works at SIXT on Cobra, an AWS-powered fleet management platform, where they focus on real-time data integrity, anomaly resolution, and reporting workflows that directly support operational and revenue decisions.”

Drashti Magia

Screened

Junior AI Engineer specializing in LLMs, multimodal ML, and applied machine learning

San Jose, CA3y exp

“Software engineer with a disciplined, production-minded approach to AI-driven development: uses ChatGPT, Claude, GitHub Copilot, and scoped coding agents to accelerate delivery without giving up architectural judgment. Notably applied a multi-agent workflow on ClinicOps Copilot, using agents for planning, Bedrock/RAG scaffolding, and failure testing while personally owning architecture, grounding quality, and end-to-end review.”

“Software engineer using AI pragmatically to accelerate development while keeping human review central to quality. Has hands-on experience applying AI and lightweight multi-agent workflows in a microservices environment spanning Java Spring Boot APIs, React modules, and Kafka event flows, with strong emphasis on architecture validation and production safeguards.”

“iGaming product leader with 11 years of Product Owner experience, spanning QA automation (built a testing framework) through BA and ultimately PO for an online poker team for nearly 6 years. Has shipped and managed live web/mobile/tablet games and worked closely with compliance/UKGC on game certification and launches, using BI/data and player feedback to prioritize features and F2P retention mechanics (tournament ticket funnels, quests).”

“Engineering leader who delivered a Magento-to-Shopify rebuild ahead of schedule while maintaining 100% team retention over 4 years at Hydrobuilder Holdings. Also built and ran a concert-listing platform (TourVolume) in production for 12+ years (Webby Honorable Mention) and later open-sourced the full codebase. Deep experience in auth/API platforms on AWS, including moving critical auth services from Lambda to ECS to eliminate cold-start latency.”

sai anuragh Sangoju

Screened

Mid-level AI/ML Engineer specializing in fraud detection, credit risk, and NLP

Dallas, Texas4y exp

“Built and deployed a production LLM-powered university support chatbot on Azure using a RAG pipeline, focusing on reducing hallucinations, improving latency, and handling ambiguous queries via confidence checks and clarification prompts. Also has hands-on orchestration experience (Airflow/Azure Data Factory), including hardening a demand-forecasting ingestion workflow with sensors, retries, and automated alerts, and uses a metrics-driven testing/monitoring approach for reliable AI agents.”

Mark Wlodawski

Screened

Senior Unity Developer specializing in AI/LLM systems and multiplayer VR

Orlando, FL11y exp

“Backend/data engineer focused on AWS-native Python systems: built a FastAPI microservice on ECS/Fargate serving real-time analytics at millions of daily requests with strong reliability (OAuth2/JWT, retries/timeouts, correlation IDs) and autoscaling. Also delivered Glue/PySpark ETL pipelines to curated S3 Parquet/Athena with schema evolution + data quality controls, owned Airflow pipeline incidents, and has a track record of measurable performance and cost optimizations (e.g., ~80%+ query latency reduction; reduced logging/NAT/Fargate spend).”

“Built a production RAG chatbot for Worcester Polytechnic Institute that indexes 500+ webpages using FAISS + Llama 3, with strong grounding/hallucination controls (confidence thresholds and citations). Also has internship experience orchestrating multi-step ETL pipelines with AWS Step Functions and delivered a 30x faster fraud/claims triage workflow at Munich Re using association rules and stakeholder-friendly dashboards.”

“Built and deployed a production LLM-powered RAG knowledge system to unify operational/policy information across PDFs, wikis, and databases, emphasizing auditability and low-latency/cost performance. Improved answer relevance at scale by moving from pure vector search to hybrid retrieval with metadata filtering and reranking, and partnered closely with healthcare operations/compliance to define acceptance criteria and human-in-the-loop guardrails.”

Susheel Thimlapur

Screened

Mid-level Full-Stack Engineer specializing in web applications and cloud systems

Bloomington, IN4y exp

“Software developer at Indiana University who built a phishing training platform using TypeScript/React, Node, GraphQL, and DynamoDB, including an admin tool to monitor student completion and send automated reminder emails. Also created TechRent, an IU-only electronics rental marketplace concept focused on improving security by restricting access to university students.”

“Candidate has hands-on experience at Cognizant building production-grade automation and integration solutions across Python ML services, Java microservices, Kafka, and Selenium-based UI testing. They stand out for a strong reliability mindset—covering failure modes, observability, flaky test hardening, and translating ambiguous payment-system business processes into resilient end-to-end automated workflows.”

“Healthcare-focused ML/AI engineer who has built production voice agents and clinical question-answering systems end-to-end, from experimentation through deployment, observability, and iteration. Particularly strong in making LLM systems reliable in real workflows via RAG, fine-tuning, guardrails, evaluation pipelines, and shared Python tooling; cites ~20% clinical QA accuracy gains and ~40% faster physician decision turnaround.”

“Full-stack engineer with payments/settlement domain experience who modernized a payment tracking workflow from REST to GraphQL and delivered a production payment status dashboard using Next.js App Router + TypeScript. Strong in performance and reliability work (Postgres indexing/Explain Analyze, Redis caching, Datadog observability) and in durable event-driven processing with Kafka (DLQs, idempotency, reconciliation, event replay).”

“Group CTO at Airobod who combines executive-level engineering leadership with hands-on technical depth across architecture, cloud, performance debugging, and AI-enabled platforms. He has led platform modernization, scaled engineering organizations in high-growth environments, and implemented rigorous multi-tenant SaaS architecture with zero cross-tenant data leaks over 12 months.”

“Full-stack developer who has built portfolio products from scratch in healthcare and recruiting, including a clinic appointment system and a dual-role job platform. Stands out for combining ASP.NET Core, Angular, SQL Server, and JWT-based authorization with strong architectural thinking around role isolation, relational modeling, and maintainable service-layer design.”

“AI/ML engineer who led Impacter AI’s production deployment of a specialized outreach LLM (CharmedLLM) fine-tuned on GPT-4.1, cutting API costs ~40% while boosting outreach effectiveness ~60%. Built the supporting MLOps and data infrastructure (MLflow, Kubernetes, PySpark, Kafka) and has agentic AI experience from University of Dayton, using LangChain + RAG and vector search (Pinecone) to improve reliability and reduce hallucinations.”

“Senior software engineer (backend/infra) with hands-on Unity gameplay feature work, including an editor-time page-generation and multilingual pipeline that renders gamebook pages as textures for instant 3D page flips. Combines immersive UX techniques (mask textures + custom shader hover feedback) with strong multiplayer/networking and scalable infrastructure thinking (latency, prediction, security, autoscaling).”

“Customer-facing application security/support professional who helps teams operationalize SAST/DAST/SCA in CI/CD, reduce false positives, and prioritize remediation by business risk. Has hands-on experience troubleshooting intermittent pipeline failures (rate limiting/timeouts under parallel load) using logs/metrics/traces, and driving durable outcomes via runbooks/KB documentation and phased security rollouts across stakeholders.”

Mohammed Saalim Kartapillai

Screened

Senior Backend/Full-Stack Engineer specializing in data platforms and cloud microservices

Chicago, Illinois7y exp

“Backend engineer who built and shipped an end-to-end AI outreach product (LazyMails) combining a LinkedIn-scraping Chrome extension with a FastAPI/Postgres backend and Gemini-powered email generation, achieving major personal productivity gains. Also has enterprise experience at TCS on Humana’s 500k+ user wellness platform running Kubernetes microservices with Azure DevOps CI/CD, plus Kafka-based real-time eligibility event streaming and GitOps-driven operations.”

Xinyu Li

Screened

Junior Software Engineer specializing in backend systems and AI/LLM RAG platforms

San Jose, CA2y exp

“Full-stack engineer who built and operated a data-driven analytics platform using Next.js App Router/Server Components and TypeScript, owning post-launch monitoring and performance/stability work. Demonstrated measurable wins in analytics performance (e.g., cutting query latency from ~1s to ~200ms) through indexing, query-plan analysis, and precomputation/caching, and has experience designing durable multi-step backend workflows with retries, idempotency, DLQ, and time-correct ordering.”

“Application-focused software engineer working on AI-heavy products, with hands-on experience building end-to-end document processing, retrieval, and configurable workflow systems. Particularly strong in combining React/TypeScript UX, FastAPI/Postgres backend design, and LLM workflow reliability improvements through validation, prompt iteration, and reusable abstractions.”