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Vetted JavaScript Professionals
Pre-screened and vetted.
Anand Madhusoodanan
Executive HR Tech & Salesforce Architect specializing in AI-driven recruiting automation
“Co-founder of an HR tech startup who took an LLM-centered skill intelligence engine from prototype to production to deliver explainable, skill-based resume insights as an alternative to black-box ATS screening. Previously worked in consulting (Deloitte, Stand Up, Brilio), with experience in technical demos/workshops, pre-sales scoping, and supporting large deal cycles (including a ~$1M UK automotive client).”
Travoy Spelling
Senior Data Scientist / ML Engineer specializing in GenAI, LLMs, and NLP
“ML/NLP engineer focused on production GenAI and data linking systems: built a large-scale RAG pipeline over millions of support docs using LangChain/Pinecone and added a LangGraph-based validation layer to cut hallucinations ~40%. Also built scalable PySpark entity resolution (95%+ accuracy) and fine-tuned Sentence-BERT embeddings with contrastive learning for ~30% relevance lift, with strong CI/CD and observability practices (OpenTelemetry, Prometheus/Grafana).”
Aaron Li
Junior AI/ML Engineer specializing in production LLM systems and RAG
“LLM/document AI engineer who owned a production-grade contract extraction pipeline at CORAMA.AI, ingesting PDFs and dynamic JavaScript sites from 1,000+ government sources. Built a hybrid deterministic+LLM system with two-phase prompting, Pydantic guardrails, confidence scoring, and human-in-the-loop review—cutting error rates from ~35% to <5% and processing 50k+ documents at ~95% accuracy. Also built clinician-in-the-loop orchestration in research, reducing manual labeling time from 3–4 hours to ~50 minutes.”
Cornelius O'Donnell
Director-level Engineering & Program Leader specializing in AI product platforms
“Technical Program Manager and one of three internal "founders" of HP’s Hardware-as-a-Service home printer subscription initiative, spanning DTC shipping, simplified setup, ink replenishment, and warranty coverage. Led roadmap definition/execution, scaled delivery rapidly to 15+ scrum teams (including vendors) with SAFe-like coordination and shared engineering standards, and drove key architecture trade-offs (building an interim subscription management service) to accelerate time-to-market by about a year.”
Akanksha Agrawal
Mid-Level Full-Stack Software Engineer specializing in event-driven data platforms
“Backend engineer with SAP experience modernizing a legacy Flask/PostgreSQL product master data platform into a modular, stateless, containerized service with Kafka-based background processing and improved observability. Also has hands-on academic/side-project experience operationalizing ML (NLP retrieval with TF-IDF/BERT via FastAPI and CV lane-edge detection inference APIs using PyTorch).”
Vismay Patel
Senior AI & Machine Learning Engineer specializing in NLP, GenAI, and MLOps
“ML/GenAI practitioner with healthcare domain depth who built and deployed a production cervical-cancer EMR classification system using a hybrid rules + medical BERT approach, optimized for high recall under severe class imbalance and PHI constraints. Experienced running end-to-end production ML/LLM pipelines with Apache Airflow (validation, promotion/rollback, monitoring, retraining) and partnering closely with clinicians to calibrate thresholds and implement human-in-the-loop review.”
ChinmaySanjay Kawle
Junior Software Engineer specializing in cloud developer tools and backend APIs
“Summer intern on AWS Lambda tooling team who shipped Finch support in AWS SAM CLI, adding OS/runtime detection and robust fallback behavior to preserve Docker compatibility across developer environments. Also built an end-to-end RAG system for querying arXiv quantitative finance papers using Postgres/pgvector with two-stage retrieval, citation-grounded prompting, and rigorous evaluation loops driven by IR metrics and user feedback.”
Rishitha Madipelli
Mid-level Software Engineer specializing in cloud-native distributed systems and streaming data
“Backend/product engineer with Tesla experience building and operating a real-time OTA update monitoring and fleet analytics platform at massive scale (telemetry from 3M+ vehicles). Delivered end-to-end systems across Kafka-based ingestion, TimescaleDB/Postgres analytics modeling, FastAPI/GraphQL APIs, and React/TypeScript dashboards, and handled production scaling incidents on AWS EKS during major rollout spikes.”
Anu Baluguri
Mid-Level Software Engineer specializing in cloud-native microservices and event-driven systems
“Full-stack engineer with production experience at Atlassian and Zoho, spanning GraphQL federation, React/TypeScript frontends, and cloud-native AWS/Kubernetes operations. Built and operated a federated GraphQL gateway with Terraform + CI/CD + observability, delivering major latency and integration-time improvements, and also designed high-volume Kafka data pipelines (10M+ events/day) with strong reliability guarantees.”
Lejia Mu
Intern Game Developer specializing in Unreal Engine 5 systems and virtual production
“UE5 gameplay animation developer focused on building and optimizing full character Animation Blueprint stacks (locomotion + jump/fall/land, montages, linked anim graphs, and layered procedural IK). Has hands-on experience debugging tricky interaction IK issues (e.g., 180-degree turn misalignment) and improving runtime performance using Unreal profiling tools and conditionalizing IK/Control Rig evaluation.”
Saiteja Gaddam
Mid-Level Data Engineer specializing in cloud data platforms and streaming analytics
“Data engineer (Intuit) who owned an end-to-end telemetry and subscription analytics platform processing ~22M events/day, built on Kinesis/S3/Glue/Spark/Airflow/Redshift. Strong focus on reliability and data quality (schema drift controls, quarantine layers, idempotent reruns) and performance tuning, achieving a reporting latency reduction from ~15 minutes to under 4 minutes while enabling revenue and churn analytics for business teams.”
Ranganayak Meravath
Mid-level Generative AI Engineer specializing in RAG, agentic copilots, and regulated AI
“Senior engineer who built and productionized an Azure-based Enterprise AI Copilot for financial/compliance teams, focused on grounded, auditable answers with citations to reduce hallucinations in regulated workflows. Experienced designing multi-step agent orchestration and improving reliability through targeted iterations (e.g., fixing chunking/parsing to materially improve citation accuracy), plus building defensive pipelines for messy ERP/operational finance data.”
Hari Kiran Reddy Rommala
Mid-level Full-Stack Software Engineer specializing in cloud and data platforms
“Full-stack engineer with experience spanning Amazon IMDb and Northeastern’s NeuroJSON portal, combining consumer product work with complex scientific data applications. Built IMDb’s streaming providers feature—described as the company’s most impactful feature of 2023—and has hands-on experience with React/Angular, GraphQL, AWS, Python services, and production monitoring.”
Prafull Prajapati
Senior Backend Software Engineer specializing in cloud, microservices, and AI systems
“Built an AI-powered job outreach application for his own job search and took it from idea to production use, owning architecture, FastAPI backend, retrieval/generation pipeline, frontend workflow, deployment, and iteration. Especially compelling for teams needing a pragmatic full-stack engineer who can turn LLM-based product ideas into usable, maintainable tools with measurable workflow impact.”
Chitra Uppalapati
Entry-level Software Engineer specializing in full-stack and machine learning applications
“Built production Python data integrations and dashboard automation for incident analytics, with a strong focus on data quality, observability, and reliability for leadership-facing reporting. Also translated an ambiguous manual creator evaluation process at startup Spring into an automated predictive scoring feature, showing a blend of backend data engineering, test automation, and cross-functional product thinking.”
Whitney Asante
Senior Ad Operations Specialist specializing in digital tagging and campaign trafficking
“Ad operations-focused paid media candidate with broad exposure across major DSPs and ad servers, including DV360, AppNexus, The Trade Desk, Amazon DSP, CM360, and Sizmek. Their experience centers on campaign setup, tagging, QA, reporting, and diagnosing tracking/viewability issues rather than owning budget strategy, making them potentially strong for execution-heavy media operations roles.”
“Built end-to-end LLM/RAG systems for biological data and scientific literature analysis in a drug discovery setting, helping researchers explore disease insights and treatment hypotheses faster. Combines applied GenAI product work with strong production engineering, including monitoring, retrieval optimization, reusable Python services, and scalable deployment on AWS/Kubeflow.”
Alex Ridore
Director-level Creative Technologist specializing in front-end interactive experiences
“Design-technologist with both UX and front-end development depth, spanning high-impact brand launches and regulated pharma sales tools. Led the experience direction and technical implementation support for DuPont's Kevlar product site—featuring Three.js, AEM, and advanced motion design—which generated strong lead capture and won an Effie, and also improved Eli Lilly IVA delivery by building a grunt.js workflow that reduced update cycles from a week to just a few days.”
Pavan Kishore Ramavath
Intern Software Engineer specializing in machine learning and backend systems
“Built an AI-powered medical coding system at Clinpex that mapped 88,000+ clinical terms to standardized codes, achieving about 86% accuracy and cutting manual review time by over 80%. Brings hands-on backend ownership in a healthcare AI setting, with experience using semantic retrieval, LLM validation, and human review to handle ambiguity and reliability in a regulated domain.”
Anveshvarma Dantuluri
Mid Backend Software Engineer specializing in FinTech platforms
“Frontend-leaning full-stack engineer with hands-on experience building financial operations and transaction monitoring products from 0→1 through production scale. They stand out for owning React UI architecture, backend/API integration, and data-layer performance decisions while making pragmatic startup tradeoffs and improving features post-launch based on latency, error, and user feedback.”
Atharva Dani
Mid-level Full-Stack Engineer specializing in React and Go applications
“Engineer with hands-on experience using AI coding tools like Claude Code and Augment in daily development, combined with real-world distributed systems work at Arista Networks. Built or worked on a Go-based platform that separated RBAC, audit logging, and provisioning into asynchronously communicating services, enabling scalable and independently evolving access-control workflows.”
Shreya B
Mid-level Software Engineer specializing in backend, cloud-native, and GenAI systems
“Software engineer with strong Java/Spring Boot backend depth and hands-on full-stack experience building AI-powered enterprise knowledge assistants and customer-facing order tracking systems. Stands out for combining RAG/LLM product work, event-driven microservices, and user-trust-focused product iteration, including shipping prototypes that became the basis for broader production workflows.”
Aakash Khepar
Mid-level Full-Stack AI Engineer specializing in agentic AI systems
“Full-stack engineer with strong ownership across production SaaS and AI agent systems, including a multi-tenant enterprise analytics product at Fractal Analytics and an archive intelligence platform for a real nonprofit. Stands out for combining deep backend/system design, secure AI/RAG implementation, and rapid zero-to-one execution—plus multiple hackathon wins and leadership roles.”
Sai Anuhya Bandi
Mid-level Full-Stack Engineer specializing in AI-driven data platforms
“Full-stack engineer with 5+ years of experience who built real-time data visualization and analytics systems at Uber, spanning React/TypeScript frontends, Node/GraphQL services, Kafka pipelines, and PostgreSQL. Particularly compelling for teams needing a hands-on builder who can turn ambiguous customer needs into scalable products, and who has also applied RAG with LangChain/OpenAI over 1.8M support files to surface actionable insights.”