Vetted Elasticsearch Professionals

“Software engineer intern at Nutanix who independently shipped and maintained an internal smoke-test/failure-analysis dashboard, integrating failure data from multiple upstream systems (e.g., Jira, Jenkins, CircleCI) via REST APIs. Also has prior data-science experience building Postgres-based asset management analytics with automated reporting and indexing for faster time-series retrieval.”

“Undergraduate robotics researcher who built a crowd-aware motion planning system to navigate safely and efficiently through dynamic pedestrian environments, implementing the full pipeline in ROS (move_base, global planning, SLAM/localization) and validating via 2D crowd simulation. Also brings modern software delivery experience from web apps, including Docker/Kubernetes-based cloud deployment and CI/CD with automated testing.”

“Full-stack developer who built a learning management web app end-to-end using React, Spring Boot, and MySQL, integrating APIs via Axios and validating/testing with Postman. Has experience handling data-heavy workloads (courses, quiz results) and improving performance with pagination, and is comfortable designing microservice-style endpoints with CI/CD considerations.”

Sakshi Dinesh Deore

Screened

Mid-level Software Engineer specializing in AWS, DevOps automation, and data platforms

Bellevue, USA3y exp

“Engineer with Securonix experience deploying and operating production microservices and real-time data-processing systems at high throughput. Led AWS infrastructure, CI/CD, monitoring, and customer-driven customization for a threat-report classification solution, including rule adjustments and model retraining based on live client feedback.”

“Backend/data platform engineer who owned a production merchant-activity aggregation and event publishing system processing ~500k merchants daily. Built a Snowflake-based daily KPI summarization pipeline orchestrated via AWS Glue/SQS and an ECS Spring Boot publisher that encrypts and publishes events to Kafka, with strong operational monitoring and reconciliation. Drove major scalability wins (10x throughput) via caching around encryption/key-management and designed selective reprocessing to handle late-arriving data cost-effectively.”

“Backend/data-systems SWE (2 years) who has built production ETL/streaming workflows (Kafka, Debezium, Elasticsearch) and troubleshot real SQL performance regressions caused by indexing/type issues. Also ships full-stack personal projects in Next.js App Router + TypeScript with Postgres, emphasizing reliability via constraints, idempotency, and strong observability (Grafana/Kibana).”

“Built and shipped a production LLM-powered multi-agent system that autonomously generates and publishes YouTube videos end-to-end (trend discovery, script writing, image/caption generation, timestamped video assembly). Emphasizes production readiness with extensive automated testing, Redis/Postgres/TimescaleDB state orchestration, and Prometheus/Grafana monitoring, reporting ~100x faster content production and improved engagement/viewership.”

Abhirup Chakraborty

Screened

Junior Software Engineer specializing in backend systems, AI, and search

Champaign, IL3y exp

“Built a complex graph-based search engine to find connections between people and has hands-on experience designing multi-agent coding pipelines that move features through implementation, test generation, testing, and sanity checks. Stands out for treating AI agents like an engineering team, with shared-memory coordination, queue signaling, and completeness-focused guardrails to improve reliability and reduce ambiguity.”

“Senior engineering leader with over 20 years of management experience and a hands-on background leading large-scale SaaS, eCommerce, CRM, and customer data platform systems serving millions of users. Stands out for combining deep technical architecture leadership with org-scale people management, including solving multi-tenant SaaS scaling issues, driving self-service product improvements from support patterns, and building governance models for cross-functional delivery.”

“Built a real-time fraud monitoring dashboard in React/TypeScript for high-frequency financial data, with a strong focus on preventing UI lag that could cause analysts to miss costly fraud patterns. Demonstrates deep frontend performance expertise across batching, memoization, virtualization, profiling, and browser layout optimization, plus some graph/visualization work involving layout stabilization and edge bundling.”

“Full-stack engineer with early-stage startup experience at Compass, working across backend services, data pipelines, and React applications in a fast-moving real estate platform. Stands out for combining hands-on systems work—like a Kafka/Python ingestion pipeline that cut latency 35%—with product impact, including dashboard workflow changes tied to a 12% lift in lead conversion.”

“Senior engineering leader who scaled a global organization from 15 to roughly 100 people and operates comfortably at both executive and hands-on architecture levels. Has led SaaS platform improvements, AI-based compliance workflow automation with LLM observability, and consumer-facing product modernization using analytics-driven UX decisions.”

“Engineering leader (player-coach) recently at Autodesk driving a major sales-motion transformation spanning account hierarchy, commissions/quotas, and downstream financial/sales forecasting impacts. Led cross-functional design with enterprise architects and shipped the end-to-end release, using POCs and Anaplan what-if modeling to validate a risky hierarchy change while coordinating delivery across India/Singapore teams and instituting structured Jira-based tech debt/support tracking and automation (dbt, GitHub Copilot).”

“ML/AI engineer with hands-on ownership of both classical ML and GenAI systems in production. They built an end-to-end churn prediction service on AWS and also shipped RAG-based document search/summarization features, with clear experience in monitoring, hallucination reduction, cost/latency optimization, and creating shared Python/LLM infrastructure used across teams.”