Vetted Apache Maven Professionals

“Built and deployed a production LLM-powered document Q&A system using a strict RAG pipeline (LangChain-style orchestration + FAISS) to help users query large internal document sets. Demonstrates strong reliability focus through hallucination mitigation, curated offline evaluation with grounding checks, and production monitoring (latency/fallback rates) plus stakeholder alignment via demos and business metrics.”

Mudit Devenkumar Choksi

Screened ReferencesModerate rec.

Junior Full-Stack Software Engineer specializing in web apps, automation, and cloud systems

Louisville, KY2y exp

“Engineer with hands-on experience owning end-to-end industrial automation deployments and real-time data systems. Most notably led a multi-million dollar warehouse automation implementation that reduced manual intervention by 25%, while also building streaming text analytics pipelines and strengthening production reliability through robust observability and pipeline controls.”

“Backend Java developer who built an end-to-end upcoming payments feature: Spring Boot/Hibernate microservices with MySQL query/index optimization and Kafka event publishing, plus a web UI timeline component enabling users to view, skip, and edit scheduled payments with clear status indicators.”

“Full-stack/product-leaning engineer in logistics and high-traffic portals who ships production AI features: built an AI-assisted shipment status Q&A system using Pinecone + GPT-4 and a high-volume Python ingestion pipeline (500K+ records/day), delivering 35% fewer support tickets and cutting resolution time from 11 to 4 minutes. Also led a legacy Angular-to-React/TypeScript rebuild that boosted Lighthouse performance from 60 to 90, and has hands-on AWS EKS operations experience including resolving a 3x traffic scaling incident.”

“Full-stack engineer who has delivered production customer analytics/dashboard features using Next.js App Router + TypeScript on the frontend and Java Spring Boot microservices on the backend. Demonstrates strong production ownership (monitoring latency/error rates/adoption) plus hands-on performance work across React rendering and Postgres query/index optimization, and has implemented Temporal-like durable workflows with retries and idempotency.”

Ratinder Joshi

Screened

Intern Full-Stack Software Engineer specializing in AI and SaaS platforms

Remote1y exp

“Built Syntriq, an AI-assisted deviation investigation platform for pharmaceutical manufacturers, owning the full stack from a 13-stage Python/FastAPI AI pipeline to a React report editor with source traceability. Stands out for combining strong technical execution with deep user discovery in a highly regulated FDA-sensitive domain, and for making pragmatic product decisions based on real QA investigator workflows.”

“Full-stack engineer from Clairvoyant who led end-to-end delivery of a cloud-native, event-driven platform: Spring Boot microservices + Kafka real-time streams with an Angular UI, migrated and containerized on AWS, and automated CI/CD with Jenkins/Maven/Git. Demonstrates depth in distributed consistency challenges (partitioning, consumer lag/duplicates) and database performance tuning across SQL/NoSQL under heavy workloads.”

Annie Suzan Edwin Arokiaraj Caroline

Screened

Junior Full-Stack Software Engineer specializing in distributed systems and data pipelines

Tempe, AZ1y exp

“Backend engineer with hands-on experience building distributed data and API platforms (Kafka + Neo4j on Kubernetes), including processing 3M+ NYC taxi trip records and achieving sub-second graph analytics queries. Strong focus on reliability and performance in Python/FastAPI systems—async refactors, caching, timeouts/retries, feature-flagged rollouts, and JWT/RBAC security for production services.”

“Candidate is actively using AI-assisted development tools, including MCP server integrations with Copilot, to generate boilerplate test scripts, validate code standards, and handle package updates. They also have hands-on experience choosing different agents based on task requirements and serving as an admin for AI tool access.”

“Software engineer with a strong builder mindset who has worked across ML, backend, and frontend systems. Notably built an AI-driven predictive autoscaler for Kubernetes from scratch using Prometheus, TensorFlow, Flask, and Spring Boot, and also delivered customer-facing automation features in financial document processing by working directly with auditors to translate domain rules into product logic.”

“Game QA professional with AAA open-world shipping experience, owning high-impact quality risks like save-data corruption, progression blockers, performance drops, and multiplayer desync. Demonstrates strong systems thinking and exploit prevention (e.g., reproduced and helped fix a reward-duplication race condition using network interruption + rapid input), with disciplined JIRA/TestRail workflows and evidence-driven bug reporting.”

“Cloud/DevOps-focused engineer with hands-on experience building Azure DevOps CI/CD pipelines for containerized applications deployed to AKS, including security scanning, approvals, versioned artifacts, and rollback. Also implemented Terraform-based IaC for Azure (VNets/subnets/NSGs/AKS) with modular design, remote state/locking, and drift detection; resolved a real deployment outage caused by an Azure RBAC permission change.”

Avanishika Revelli

Screened

Junior Software Engineer specializing in backend, cloud, and robotics automation

2y exp

“Graduate Research Assistant in Robotics at Arizona State University who built an end-to-end LLM-driven task execution framework enabling collaborative robots to convert high-level natural language instructions into safe, executable ROS actions. Implemented robust monitoring, failure detection, and automatic replanning, and addressed real-world issues like timestamp/frame-transform mismatches and heterogeneous robot interoperability using adapter nodes.”

“Built and shipped a production LLM-powered incident response agent for a microservices platform, automating alert triage and safe remediation recommendations with strong guardrails (RAG grounding, structured JSON outputs, rule-based validation, and human-in-the-loop). Implemented state-machine orchestration (Redis/Kafka), comprehensive eval/monitoring, and an error categorization pipeline that cut hallucination errors ~40% and reduced MTTR ~30%.”

Revanth P

Screened

Mid-level DevOps Engineer specializing in AWS, Azure, Kubernetes, and GenAI infrastructure

Walnut Creek, CA4y exp

“Database/platform engineer with stronger hands-on experience in AWS and Azure than GCP, but able to speak credibly about cloud database architecture, automation, and reliability engineering. They led an on-prem MySQL to RDS/DynamoDB migration, built Terraform/Python-based zero-touch database operations, and described a performance incident where latency dropped from 2s to under 300ms while supporting 2x traffic.”

Nikita Sipeikin

Screened

Mid Backend Java Developer specializing in high-load FinTech systems

Bali, Indonesia5y exp

“Java developer with hands-on experience using AI coding tools heavily in day-to-day development, estimating roughly 60% AI-generated output in a recent shipped feature. Brings practical debugging and testing experience, including performance testing and resolving Spring Boot circular dependency issues through architectural changes.”

“Full-stack engineer with hands-on experience building end-to-end applications using Java/Spring Boot and React, including Dockerized deployment and RabbitMQ-based messaging. Worked on a high-volume payment processing system at Alacriti, focusing on performance (query optimization, caching) and reliability with monitoring via AWS CloudWatch.”

Charmi Dharmendrakumar Parmar

Screened

Mid-Level Software Engineer specializing in full-stack and cloud-native systems

Alpharetta, GA4y exp

“Backend/full-stack engineer who owned a cloud-native, AWS-based microservices backend for an HRIS product used by ~10,000 users, including onboarding and workflow orchestration. Strong production focus on event-driven architecture, idempotency/retries, observability, and developer-friendly API design (OpenAPI, versioning, JWT), plus hands-on Selenium automation for resilient checkout-style flows.”