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Vetted Kubernetes Professionals
Pre-screened and vetted.
Rakesh Thota
Mid-level Data Engineer specializing in multi-cloud real-time data pipelines
“Data engineer with healthcare/clinical trial domain experience who owned a 100TB+/month AWS pipeline end-to-end (Glue/S3/Redshift/Airflow) and drove measurable outcomes (20% lower latency, 99.9% reliability, 40% less manual reporting). Also built production data services and API-based ingestion on GCP (Cloud Run/Functions/BigQuery) with strong validation, versioning, and safe migration practices, and launched an early-stage RAG solution (LangChain + GPT-4) for researchers.”
Lerone Pieters
Senior Data Engineer specializing in cloud data platforms and real-time analytics
“Data/analytics engineer focused on finance and e-commerce integrations, building end-to-end pipelines and services across Odoo, QuickBooks, Snowflake, and Tableau. Replaced a costly third-party Walmart connector with a serverless AWS Lambda pipeline deployed via Terraform/GitHub and monitored with CloudWatch/Datadog, and shipped a bi-directional Odoo↔QuickBooks invoice sync with distributed locking plus Slack-based finance approvals.”
Saiprasad Barkam
Mid-level Data Engineer specializing in cloud ETL and streaming data pipelines
“Data engineer in healthcare/clinical data platforms (HarmonCare) who built and operated an end-to-end lakehouse pipeline ingesting HL7/FHIR at ~2–3M records/day on AWS (Glue/Lambda/S3/Spark) and serving trusted datasets in Snowflake. Implemented strong validation/reconciliation gates and a data quality framework that reduced discrepancies ~40%, plus CI/CD (GitHub Actions/Terraform) and monitoring (Airflow/CloudWatch).”
Estelle Marcella Bouopda Meba
Mid-level Full-Stack Developer specializing in React and RESTful APIs
“Frontend React/TypeScript engineer who built a text-to-speech feature from scratch end-to-end, including frontend-backend communication and testing. Experienced improving existing React codebases through refactoring into reusable components, custom hooks, and performance optimizations, and collaborates closely with product/design using Figma, design systems, and early previews via staging/Storybook.”
Vivekananda Reddy
Mid-Level Full-Stack Software Engineer specializing in Java, React, and AWS
“Backend engineer focused on cloud-native microservices on AWS, owning Python/Flask ingestion services integrated with S3/Lambda and deployed via Docker/Kubernetes with CI/CD. Has led phased migrations from manually managed EC2 setups to automated CloudFormation + pipeline-driven releases, and designed event-driven near-real-time pipelines with idempotency, retry/backoff, and strong observability.”
Anay Dongre
Junior Machine Learning Engineer specializing in GenAI and LLM fine-tuning
“Robotics software engineer focused on hard real-time autonomy for legged robots, building a quadruped navigation stack that combines vision SLAM with MPC and maintains a deterministic 500Hz control loop. Deep performance optimization experience across CUDA (sub-2ms perception latency), ROS 2/DDS real-time tuning, and motion planning (cut 500ms spikes to sub-5ms). Also designed distributed ROS 2 + Zenoh communications between quadrupeds and aerial drones and validated robustness under lossy wireless conditions.”
Sachin Dulla
Mid-level AI/ML Engineer specializing in NLP, fraud detection, and MLOps
“Built and deployed a domain-specific LLM chatbot for research/support, cutting manual effort by ~50%. Demonstrates strong applied LLM engineering: RAG, prompt grounding with citations and fallbacks, embedding/top-k tuning, and production monitoring (confidence, latency, feedback loops). Experienced orchestrating agent workflows with LangChain-style pipelines and continuous evaluation to maintain reliability.”
Sai Nikhil Kanchukatla
Senior Software Engineer specializing in Golang microservices and IAM/SSO
“Backend engineer with experience at DigitalOcean and BNY Mellon, specializing in secure, highly available authentication and API platforms. Built an enterprise SSO system integrating Okta via OIDC with resilience patterns (gRPC contracts, circuit breakers, Kafka) and strong encryption, and led a careful monolith-to-Golang microservices migration using shadow traffic, dual writes, and feature flags to preserve data integrity.”
Shrinivas Bhusannavar
Mid-level AI Engineer specializing in agentic LLM systems and RAG platforms
“Built and shipped Serrano AI, a multi-tenant SaaS conversational AI platform that automates Odoo ERP workflows and lets ops/finance/supply-chain teams query ERP data in natural language. Implemented a multi-agent architecture (LangChain/LangGraph/CrewAI) with hybrid RAG over ERP schemas, deployed on Heroku/Vercel with production observability, cutting reporting time by ~80% while addressing hallucinations, latency, and schema complexity.”
Hy Serure
Executive Technology Leader & Architect specializing in enterprise digital transformation
“Longtime S-Corp founder (20+ years) who evolved from running a web agency to becoming a Shopify expert contracted by agencies/brands to upskill teams and lead enterprise eCommerce builds. Recently built and launched a payment-links/QR-code web app in weeks that gained 20 users on day one without advertising; now looking to pivot toward building a scalable product business not tied to hourly contracting.”
Emmanuel Bakwowi
Senior DevSecOps Engineer specializing in multi-cloud Kubernetes and CI/CD automation
“Cloud/DevOps engineer operating across AWS and Azure, running Kubernetes workloads with secure CI/CD (GitHub Actions/Azure DevOps) and Terraform IaC. Has supported AIX/PowerHA systems in hybrid environments—handling failover testing, incident recovery, and performance troubleshooting (including multipath/storage-path issues)—and has led cutovers by managing dependencies, rollback, and stabilization.”
Bhavishyasai Chigurupati
Mid-Level Data/ML Engineer specializing in Generative AI and cloud data platforms
“Built and productionized an LLM-based financial document analysis system using a RAG pipeline, including robust ingestion/chunking/embedding workflows, vector DB retrieval, and an AWS-deployed FastAPI service containerized with Docker. Demonstrates strong applied expertise in improving retrieval quality and latency at scale, plus hands-on experience debugging agentic/LLM workflows with monitoring and trace-based analysis while supporting demos and customer-facing adoption.”
Umair Khokhar
Director-level Engineering Leader specializing in AI Platforms for Enterprise B2B SaaS
“Technical leader/player-coach who architected and shipped an end-to-end computer vision pricing system for a major North American auto seller, using Go + Ray + AWS SageMaker in a low-latency distributed inference architecture. Strong in production governance (logs/tracing/guardrails/AppSec), reliability incident ownership (DNS limits affecting 20% traffic), and measurable delivery acceleration (deployment cycle 16→4 days; delivery speed 5→2 days) through process optimization and AI-assisted enablement.”
Jarin Tasnim
Staff/Lead Software Engineer specializing in distributed data and ML platforms
“Defense-domain AI engineer who built a production ReAct-style RAG system for military training data/material generation, scaling to ~1000 users and cutting generation time by 50%. Also has experience designing GPU-cluster parallel computation with PyTorch and handling production incidents involving database performance and schema design.”
Rupini Polavarapu
Senior DevOps Engineer specializing in AWS cloud infrastructure and CI/CD automation
“AWS platform/infra engineer with hands-on ownership of EKS cluster lifecycle (upgrades, node scaling, networking/ingress, and EBS-backed stateful storage) and reliability validation using Datadog plus CI/CD smoke tests. Also supported on-prem VMware environments and operated a hybrid on-prem-to-AWS setup over site-to-site VPN, including incident response and implementing change-controlled firewall processes and proactive connectivity health checks.”
Kavya Myakala
Mid-level Frontend Developer specializing in security analytics dashboards
“Built and shipped production LLM agents including an end-to-end customer support resolution system (99.9% uptime target) that improved customer satisfaction by ~18% and reduced the need to scale support headcount. Demonstrates strong agent engineering fundamentals—tool-based orchestration, schema-first structured outputs with deterministic validation, and robust eval/monitoring loops—plus experience integrating agents with messy ERP data using canonical normalization and safe fallbacks.”
Jeet Patel
Junior AI and Backend Engineer specializing in LLM systems
“AI/LLM engineer who has shipped production RAG copilots and multi-agent workflows, including a real-time Llama3 (Ollama) copilot backend handling 12k+ concurrent queries at 99.9% uptime. Deep on orchestration (Langflow/Airflow/Kubernetes), reliability evaluation (hallucination detection, p95 latency, token cost), and monitoring (Prometheus/Grafana), with demonstrated stakeholder-facing analytics delivery via Tableau.”
Lavanya Nandan Deole
Intern software engineer specializing in AI, mobile, and distributed systems
“Entry-level candidate who built NYC Lens, a real-time Gemini-based multi-agent system that processes live camera input, identifies landmarks, and returns structured contextual insights. Despite being a fresher, they show hands-on experience with deployment on Cloud Run, modular orchestration, noisy-data handling, and reliability patterns like retries, fallbacks, and explicit state management.”
Arslan Javed
Senior Machine Learning Engineer specializing in LLMs, NLP, and computer vision
“Built and owned production GenAI systems for both infrastructure automation and customer support. Most notably, they created a self-healing multi-cloud incident response system that automated 65% of tier-1 alerts and reduced application crashes by 75%, and also shipped a hybrid RAG support triage agent that automated 60% of tier-1 inquiries with human escalation guardrails.”
SaiSindhu Beeravolu
Mid AI/ML Engineer specializing in LLMs, RAG, and healthcare AI
“Healthcare ML/AI engineer with production experience at UnitedHealth Group, including an end-to-end readmission prediction system built on 50M+ patient records that improved accuracy by 18% and reduced preventable readmissions by 12%. Also shipped a clinically grounded LLM/RAG referral generator with human-in-the-loop safety controls, showing strong depth in regulated, high-stakes AI systems.”
“Built and owned a production RAG-based conversational AI system at Entera for real estate analysis, taking it from experimentation through AWS deployment, monitoring, and iterative improvement. Demonstrates strong practical judgment in retrieval design, LLM safety, and scalable Python service architecture, with measurable impact including 30-40% reduction in manual analysis time and roughly 30% better response accuracy.”
Sreeraj Chintham
Mid-level Software Engineer specializing in Python backend and AI/GenAI
“Backend/infrastructure-focused engineer building AI-agent products for small businesses, including a customer-service agent platform with intent routing, RAG over Pinecone, and external booking API integration. Has shipped Python/FastAPI services with JWT auth, versioned APIs, Docker deployments to AWS EC2 via GitHub Actions, and production monitoring with Prometheus/Grafana.”
Raghav Bajaj
Junior Software Engineer specializing in backend systems and ML applications
“Full-stack engineer with hands-on experience building and shipping production web products across AI, frontend, backend, and DevOps. Notably built an end-to-end resume-job matching platform during an internship that processed 1000+ resumes/day and cut recruiter screening effort by 60%, and later shipped an internal operations dashboard at CHS with measurable performance gains.”