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Vetted Kubernetes Professionals
Pre-screened and vetted.
Piyush Rajendra
Mid-level AI/ML Engineer specializing in production RAG systems and MLOps
“Built and deployed a GPT-4 + Pinecone RAG system that lets users query large internal document collections with grounded, cited answers. Demonstrates strong applied LLM engineering (chunking experiments, hallucination controls, metadata recency boosting) plus production-minded evaluation/monitoring and performance tuning (rate-limit mitigation via pooling/batching). Also effective at translating complex AI concepts to non-technical stakeholders through prototypes and live demos, helping secure client sponsorship.”
Daanesh Potnuri
Mid-Level Full-Stack Engineer specializing in API-driven microservices and cloud delivery
“Software engineer with hands-on experience building a decentralized file-sharing dApp, bridging a React frontend with Ethereum smart contracts via Web3.js and integrating IPFS for decentralized storage. Demonstrates a rigorous, measurement-driven approach to performance optimization (profiling + benchmark/regression loop) and strong ownership in high-stakes environments, including Fircosoft sanctions platform optimization and rapid production hotfixes for user-impacting issues.”
Hrishi Kamal Earla
Senior Full-Stack Java Developer specializing in cloud-native FinTech microservices
“JavaScript/React engineer with hands-on open-source library contribution experience, including thoughtful PRs that improved error handling, API flexibility, and added features backed by tests and documentation. Demonstrates a profiling-first approach to UI/runtime performance (memoization, component splitting, render-path optimization) and strong community support skills—reproducing edge cases, delivering sustainable fixes, and communicating workarounds and releases.”
Varun Kothapalli
Mid-level AI/Machine Learning Engineer specializing in Generative AI, NLP, and MLOps
“Built a production LLM/RAG document analysis system for large financial documents (credit reports/PDFs) to help business analysts extract insights faster. Implemented end-to-end pipeline orchestration with LangChain, vector search (e.g., FAISS), and hallucination controls (context grounding, similarity thresholds, and no-answer fallback), delivered as a Dockerized Python API.”
Nilesh Bhoi
Mid-Level Software Engineer specializing in full-stack web apps and real-time systems
“Software engineer who has owned and improved a customer-facing quote flow in a Vue/Nuxt app, using production observability to reduce latency and improve reliability via caching and request-handling fixes. Also shipped an internal LLM Q&A tool using embeddings + RAG over approved company docs and past support tickets, with guardrails, logging, and an evaluation loop that drove retrieval/prompt improvements. Seeking ~$110k base and requires H1B transfer sponsorship.”
Sreedivya Nagalli
Junior AI/ML Engineer specializing in deep learning and full-stack ML applications
“Built and operated a production-used RAG-based AI study planner (GPT-4 + FAISS) that handled 250+ concurrent users, with real-world reliability engineering (caching, fallbacks, schema validation, Redis state, monitoring). Also has healthcare data integration experience at Medinet Analytics, standardizing messy EHR/practice-management data with canonical schemas, idempotency hashing, and compliance-grade audit trails.”
Abinav Anantharaman
Mid-level Robotics Software Engineer specializing in perception, sensor fusion, and motion planning
“Robotics/Perception Software Engineer at Berkshire Grey who built and hardened a production ROS-based perception + supervision stack for autonomous trailer-unloading robots (RGB-D + LiDAR), including grasp/geometry estimation and segmentation. Diagnosed real-time behavior issues by instrumenting ROS pipelines, then implemented runtime RANSAC-based compensation for LiDAR yaw bias and TF-window validation; also supports containerized deployment on Kubernetes and is actively porting the system from ROS1 to ROS2.”
Lakshmi Priya Ramisetty
Mid-level ML & Data Engineer specializing in GenAI, graph modeling, and fraud/risk analytics
“Built a production AI fraud/risk scoring platform at BlueArc that ingests web business/product/site data, generates text+image embeddings, and connects entities in a graph to detect reuse patterns and links to known bad actors. Optimized for scale with incremental graph re-scoring and delivered investigator-friendly explainability by surfacing the exact signals/relationships behind each score; orchestrated workflows with Airflow and GCP event-driven components (Pub/Sub, Dataflow, Cloud Run) and has recent LLM workflow orchestration experience (retrieval, prompting, scoring).”
Darshan Togadiya
Mid-level Full-Stack Engineer specializing in cloud-native web apps
“Full-stack engineer in an early-stage startup who built an EV charger monitoring and payments dashboard from scratch, owning UI/UX (Figma), React frontend, Node/Postgres APIs, and production deployment/ops (Firebase + AWS). Demonstrated measurable impact (40% fewer reconciliation errors) and strong reliability chops through multi-source energy/payment ingestion, idempotent pipelines, and CloudWatch-driven incident resolution.”
Manali Patil
Senior Software Engineer & Engineering Manager specializing in cloud backend and manufacturing MES
“Customer-facing engineer who led recurring midnight ERP data-feed/B2B integrations from prototype to production, building reusable APIs and using Hangfire for job scheduling. Known for tight weekly customer iteration, strong documentation and test coverage (80%+), and cross-functional problem-solving with Operations/Quality/NPI to resolve data-collection and manufacturing-process constraints; has 2 customers live on the integration.”
somasekhar G
Mid-level Data Engineer specializing in cloud big data and streaming pipelines
“Data engineer focused on large-scale financial data platforms, with hands-on ownership of an AWS + Databricks + Snowflake pipeline processing ~2TB/day. Strong in data quality (Great Expectations), schema drift automation, and production reliability (99.9%), plus measurable performance/cost wins (4h→1.2h, ~25% cost reduction). Also built an async Python crawling/ingestion framework with anti-bot mitigation, retries, and Airflow-driven backfills.”
Sravya Chunduri
Mid-level AI/ML Engineer specializing in LLM, NLP, and MLOps
“AI/ML Engineer with 3+ years of experience spanning RAG pipelines, MLOps, large-scale data workflow automation, and resilient Playwright-based UI automation. At Black Hawk Network and Wipro, they describe shipping production systems with strong observability and compliance controls, including reducing flaky automation failures from 30% to under 2% and automating 3+ TB/day reconciliation workflows.”
Sumanth Mereddi
Mid-level Full-Stack Engineer specializing in cloud and FinTech platforms
“Full-stack product engineer with hands-on experience shipping React/TypeScript applications on AWS serverless infrastructure with Postgres. Stands out for combining measurable performance optimization (~30% faster APIs), UX improvements that lifted activation by 25%, and pragmatic platform thinking through reusable hooks and safe multi-tenant dashboard customization.”
Varun Sharma
Mid-level AI Builder and Data Engineer specializing in GenAI and data pipelines
“Full-stack AI product engineer who personally built ViGenAir, a multimodal system that turns long-form video into ads using FastAPI, React, and agentic scoring. Stands out for handling complex 50GB+ media pipelines, re-architecting systems to eliminate OOM failures, and making opaque AI workflows usable through interactive visual UX that improved trust, speed, and retention.”
Yashwanth Repala
Mid-level Full-Stack Java Developer specializing in healthcare and enterprise platforms
“Built and shipped a production LLM-powered agent for supply chain operations that integrates ERP data and automates multi-step decision-making with tool calling, state management, and structured JSON outputs. Emphasizes production reliability (guardrails, fallbacks, monitoring, idempotency) and reports strong business impact: 40% faster decisions, 30% higher throughput, and 25% efficiency gains.”
Shyam Kumar
Junior Software Developer specializing in full-stack and backend web development
“Backend engineer with hands-on ownership of production FastAPI systems, from containerized deployment and reverse proxy setup through operations, reliability metrics, and future-state scaling plans. Also brings applied ML experience, having built and integrated a custom CNN-based fruit classification system with confidence-based human review safeguards.”
Lavanya Nallabelli
Junior Full-Stack Engineer specializing in AI-powered systems
“Backend engineer with hands-on ownership of a production POS platform, including architecture, CI/CD, Kubernetes deployment, and live incident handling. Also built a RAG-based document Q&A system using OpenAI/Anthropic with hybrid retrieval, evaluation metrics, and fallback logic, showing both traditional backend depth and practical applied AI experience.”
Eoin McDonnell
Staff Full-Stack & DevOps Engineer specializing in cloud-native platforms and AI
“Backend/data engineer focused on production Python and AWS: built FastAPI REST services and a containerized ECS Fargate + Lambda architecture deployed via Terraform/CI-CD. Strong in data engineering (Glue/S3/Parquet/RDS) and operational reliability (CloudWatch/SNS, retries, schema-evolution handling), with experience modernizing legacy SAS reporting into Python microservices using feature flags and parity validation.”
Wijdaan Khundmiri
Mid-level Full-Stack Developer specializing in AI/ML and cloud-native applications
“Full-stack/AI engineer who has shipped production systems spanning real-time analytics dashboards and an internal LLM-powered knowledge assistant. Experienced with RAG pipelines (embeddings/vector DB, semantic retrieval, query rewriting) plus evaluation loops and guardrails, and builds observable Kafka-based data pipelines monitored with Prometheus/Grafana.”
Harshitha Ayenugula
Mid Software Engineer specializing in backend and FinTech systems
“Full-stack engineer with strong ownership of complex web products, including building a real-time collaborative editor end-to-end using React, Spring Boot, WebSockets, Yjs CRDT, PostgreSQL, Redis, and Docker. Stands out for combining product delivery with production reliability and performance work, including reducing QA defects by ~25%, improving internal tool load times to under 2 seconds, and resolving latency issues in live systems.”
Paul Bailey
Executive engineering leader specializing in full-stack software and aerospace systems
“Early-stage founder with a privacy-focused concept to simplify at-home self-hosting for services like email, photos, files, and local AI. They are approaching the idea in staged phases to test traction and minimize upfront capital, and have some familiarity with the startup accelerator ecosystem through a Techstars-affiliated company.”
Surya Padmini Konjula
Mid-level Software Engineer specializing in backend, cloud, and AI for FinTech
“Senior full-stack engineer focused on AI-powered workflow automation and customer support products, with hands-on ownership from React/TypeScript UI through FastAPI microservices, retrieval pipelines, and Kubernetes deployment on GCP. Particularly strong in turning ambiguous zero-to-one AI initiatives into production systems that reduce manual operations, improve turnaround time, and remain reliable through strong orchestration and monitoring practices.”
Raahul Sallagunta
Mid Software Engineer specializing in backend microservices and Healthcare IT
“Backend and distributed-systems engineer with experience integrating LLM capabilities into clinical data workflows at CVS. Stands out for treating AI as an engineering accelerator rather than a shortcut, with strong emphasis on validation, observability, Kafka-based async pipelines, and safe multi-agent orchestration for production systems.”
David Wang
Junior Software Developer specializing in full-stack web and enterprise systems
“Frontend engineer focused on sophisticated real-time operational UIs, with experience building logistics workflow platforms used by managers, analysts, and support teams. Stands out for combining deep browser-performance knowledge with thoughtful interaction design for demanding users in correctness-critical, live-updating systems.”