Vetted Selenium Professionals

“Early-career CS/data professional with hands-on experience integrating analytics dashboards into a production MERN system, including a Redux state redesign and schema validation that delivered zero-downtime release and measurable performance gains (~30% faster APIs, 25% faster reporting). Previously a data analyst at Reliance Jio, where they extended Python-based reporting pipelines (CSV/MySQL) with automated validation and anomaly detection to improve KPI dashboard reliability and cut investigation time by ~30%.”

“Full-stack engineer focused on data-heavy platforms, building Spring Boot microservices and Angular/React dashboards end-to-end. Has hands-on experience improving large-scale API and UI performance (including cutting 8–10s response times) and ensuring cross-service consistency using Kafka, idempotent consumers, and strong validation/transaction patterns on AWS with CI/CD and observability (Prometheus/ELK).”

“LLM/RAG-focused engineer who repeatedly takes agentic workflows from impressive demos to dependable production using rigorous evals, SLOs, and deep observability. Has led high-impact incident mitigation (22-minute MTTR during a major sale) and developer enablement workshops, and partnered with sales to close a $410k ARR enterprise deal with a tailored RAG pilot (FastAPI/pgvector/Okta/InfoSec-ready).”

“Backend/AI engineer who has shipped production LLM systems end-to-end, including an AI request-routing service (FastAPI + BART MNLI + OpenAI/Gemini) that improved accuracy ~25% after launch via eval-driven prompt/category iteration. Also built an enterprise document intelligence/RAG platform on Azure (Blob/SharePoint/Teams ingestion, OCR/NLP chunking, embeddings in Azure Cognitive Search) with PII guardrails (Presidio), confidence gating, and scalable event-driven pipelines handling millions of documents.”

“Backend-focused TypeScript/Node.js engineer who owned a production microservice for transactional workflows in a React + microservices platform, integrating REST and Kafka event processing. Emphasizes operability and correctness (idempotency keys, exponential backoff retries, DLQs, centralized logging/metrics/alerts) plus strong API DX via versioning and Swagger/OpenAPI with improved error contracts based on developer feedback.”

Rasega Babu Kavitha

Screened

Mid-Level Full-Stack Software Engineer specializing in Java/Spring and React

Boston, MA4y exp

“Full-stack engineer who has shipped a real-time social engagement feature (live messaging + personalized feeds) for a career networking platform, owning everything from WebSockets/SSE and JWT+Redis auth through Docker/Kubernetes production deployment. Also built a production Flask backend for an AI-driven movie recommendation system on AWS, with strong API design (versioning/error standards) and hands-on performance tuning (Typesense +47% query improvement, Postgres indexing, Redis caching, CloudWatch-driven incident response).”

Anupam Sistla

Screened

Intern Software Engineer specializing in full-stack development, cloud, and automation

2y exp

“Robotics software engineer who built an autonomous debris-clearing rover software stack end-to-end using ROS 2, Python/OpenCV, and YOLOv3, with strong emphasis on real-time reliability (latency instrumentation, stale-data handling, watchdog fail-safes). Also implemented a Docker CI/CD deployment system for remote Raspberry Pi timelapse devices, distributing updates via AWS S3 to handle intermittent connectivity.”

“Full-stack engineer with healthcare/AI platform experience (Humana), owning an end-to-end high-risk patient prediction feature from React dashboards through FastAPI/TensorFlow real-time inference to AWS EKS operations. Emphasizes production reliability and contract-driven APIs (OpenAPI + generated TS types), plus strong data integration patterns (Kafka, idempotency, DLQs, backfills) in regulated, high-traffic environments.”

“Backend/data engineer with production experience in financial payroll, tax, and compensation platforms, building Python microservices and AWS-based data pipelines for high-volume, peak-driven workloads. Strong reliability focus (OAuth2 auth, retries/timeouts, structured logging, incident response) and proven performance wins, including cutting complex report queries from ~8 minutes to under 30 seconds.”

“Backend/data engineer with hands-on production experience across Python/Flask microservices and AWS serverless/data platforms (Lambda, DynamoDB, S3, Glue/PySpark). Demonstrated strong reliability and operations mindset (JWT/RBAC, retries/timeouts/circuit breakers, CloudWatch/SNS alerting) and measurable performance wins (SQL report runtime cut from 10 minutes to 30 seconds). Seeking ~$150k base and cannot travel for onsite meetings for the next 5–6 months due to family medical constraints.”

“Frontend engineer focused on high-scale React + TypeScript dashboards, including an internal Instagram creator/agency analytics dashboard handling extremely large datasets (1–2TB) with virtualization and performance profiling to maintain ~60fps UX. Experienced in modern state management (Redux Toolkit/RTK Query), modularizing legacy codebases into shared component libraries (Storybook), and shipping fast with feature flags plus automated QA (Playwright/Selenium).”

“DevOps engineer (State Farm) with hands-on ownership of Python backend services and data pipelines, deploying microservices and workers on Kubernetes using GitOps (Argo CD). Has led complex cloud-to-on-prem/hybrid migrations with staged cutovers and rollback planning, and built Kafka-based real-time streaming pipelines with schema governance, autoscaling, and strong observability.”

“LLM/RAG engineer who has built and shipped production assistants, including a RAG-based teaching assistant (Marvel AI) using LangChain/LlamaIndex/ChromaDB with OpenAI embeddings and Redis vector search, achieving ~30% accuracy gains and ~35% latency reduction. Also deployed FastAPI services on Google Cloud Run with observability and prompt-level monitoring, and partnered with non-technical ops stakeholders to deliver an internal policy-document RAG assistant.”

Purva Chakravarti

Screened

Senior Full-Stack Software Engineer specializing in scalable web apps, cloud, and blockchain/AI

Chino, California11y exp

“Full-stack engineer with strong production ownership across React/TypeScript, Node.js, and AWS (EC2/ECS/RDS/CloudWatch), including CI/CD, observability, and incident response. Delivered a secure RBAC workflow module end-to-end and achieved measurable gains (~30–40% latency reduction, ~50% error reduction) that lowered infra/ops costs. Comfortable in high-ambiguity startup environments—shipped a payment module within 2 days of joining with no documentation.”

Anudeep Reddy Veerla

Screened

Mid-Level Software Engineer specializing in cloud-native microservices

Boston, MA3y exp

“Built and shipped both a solo real-time multiplayer Spades game (TypeScript monorepo with shared client/server engine) and a production internal LLM-powered document Q&A tool for a SaaS company. Demonstrates strong RAG pipeline design (Pinecone + embeddings + reranking), rigorous eval/regression practices, and pragmatic data ingestion/observability work across Confluence, Notion, and messy PDFs/OCR—backed by clear metric improvements (P@1 61%→78%, escalations 40%→22%).”

Srinivasan Gomadam Ramesh

Screened

Mid-level AI/Data Engineer specializing in agentic AI and data platforms

Redmond, WA7y exp

“AI/LLM engineer who built a production resume-parsing and candidate-matching platform at Quadrant Technologies, combining agentic LangChain workflows, VLM-based document template extraction (~85% accuracy), and a hybrid RAG backend for resume-to-JD search. Notably integrated automated LLM evals and metric-based CI/CD quality gates to catch silent prompt/model regressions, and led a 3-person team across frontend/backend/testing.”

“Currently acts as a tech lead for a team of AI agents building a mobile application, with agents handling requirements, design, development, testing, documentation, and JIRA/Confluence updates. Stands out for combining multi-agent orchestration with strong human-in-the-loop review and a clear interest in AI governance and authorization controls.”

“Backend Python engineer who has built an LLM agentic tutoring/assignment helper with a custom pipeline for parsing visually complex textbooks (integrating AlibabaResearch VGT and implementing missing preprocessing from the paper), improving RAG grounding with ~90% cleaner extracted text. Also led major platform scaling work by refactoring monolithic image processing into Celery-based async microservices on AWS (GPU/CUDA + S3), and implemented Kafka streaming for payment webhooks with strict ordering, idempotency, and multi-zone fault tolerance.”

“Robotics project manager and software lead for an underwater ROV (MATE 2024–2025), building a ROS 2 Jazzy stack on Raspberry Pi and a serial Pi-to-Arduino thruster control system for a 6-thruster configuration. Also has internship experience creating automated functional test pipelines using Jenkins, Selenium, and Python, plus exposure to Isaac Sim for simulated/synthetic data generation in an embodied AI hackathon.”

“Backend engineer with Accenture and EY experience building multi-tenant financial/compliance platforms in Python/Flask. Strong in performance and scalability work across SQLAlchemy/PostgreSQL (EXPLAIN ANALYZE, indexing, N+1 fixes) and in reliability improvements using Celery + Redis. Has integrated external AI model APIs for document extraction/invoice validation with robust background processing, retries, and output cleaning.”

“Built a production lead-generation system using AI agents that researches the internet for relevant leads and integrates RAG-based contact enrichment/shortlisting aligned to existing CRM data, enabling sales reps to focus more on selling. Also has hands-on AWS data orchestration experience (Glue, Step Functions) moving raw data into Redshift and evaluates agent performance with human-in-the-loop plus BLEU/perplexity metrics.”

“QA automation engineer with hands-on ownership of both UI and API test automation, including building an API test module from scratch to validate all Swagger-exposed endpoints with positive/negative coverage and pairwise optimization. Experienced stabilizing flaky Cypress tests through improved selectors (data-cy) and API-call synchronization, and integrating tiered test suites into GitLab CI with merge/release gates plus JUnit/HTML reporting and Slack notifications.”