Vetted JavaScript Professionals

Shanmukha Koganti

Screened

Mid-level AI/ML Engineer specializing in recommender systems and edge computer vision

Bay Area, CA6y exp

“ML/AI engineer with production experience at Shopify and Intel, building a deep learning product ranking system that lifted add-to-cart ~14% and serving real-time similarity search via FAISS+Redis under <20ms latency at massive scale. Also deployed computer vision models to 100+ retail edge locations using Docker/Ansible/k3s with zero-downtime rollouts, and applies strong MLOps practices (A/B testing, canary/shadow, observability) plus performance optimization (OpenVINO, INT8).”

Pratima Singh

Screened

Senior Full-Stack Software Engineer specializing in FinTech, cloud microservices, and blockchain

Tempe, AZ10y exp

“Python/ML engineer with strong DevOps depth: built an end-to-end regime-aware stock prediction system (custom fine-tuned FinBERT sentiment + technical/macro features) delivering a 12% accuracy lift. Also implemented Kubernetes/Helm + Jenkins/GitHub Actions pipelines (including GitOps-style workflows for multi-cloud Hyperledger Besu) and improved deployment speed/stability by ~50% while addressing race conditions and image drift.”

Alex Vo

Screened

Staff Backend Software Engineer specializing in telemetry pipelines and observability

San Jose, CA3y exp

“Backend engineer from VMware focused on proprietary enterprise systems (monitoring tools, data pipelines, and APIs). Drove a ClickHouse migration POC (local to remote host) using a dual-write/cutover approach and source-level debugging across Node/driver differences during a Node 12→20 upgrade, and delivered measurable performance gains (~20% CPU/memory improvement) through batching and streaming ingestion.”

Nagarjuna Vaddineni

Screened

Mid-level Full-Stack Software Engineer specializing in cloud-native microservices and data pipelines

Seattle, WA6y exp

“Amazon backend engineer who built and operated high-scale Java Spring Boot microservices on AWS (EKS/EC2) handling millions of daily transactions, with deep experience debugging p95 latency and database/ORM bottlenecks. Shipped an AI-driven real-time personalization feature by integrating SageMaker model inference end-to-end with low-latency caching and graceful fallbacks, and designed robust order/payment orchestration with retries, compensations, and DLQ-based escalation.”

Shruti Krishnagiri

Screened

Executive Engineering Leader & Technical Founder specializing in AI automation platforms

San Francisco Bay Area, California20y exp

“Founder/CTO who built and shipped a consumer subscription-bundling platform end-to-end (architecture, implementation, testing) and scaled it to thousands of customers and major partners. Previously led a major reliability overhaul at Chan Zuckerberg Initiative for a Google-Docs-like ed-tech product—boosted observability, introduced incident management, and migrated to a Docker-based scalable architecture. Heavy user of AI tools (Cursor/Claude) for development, testing, and code review, with a strong bias toward lightweight, fast-moving execution.”

Sai Dinesh Pusapati

Screened

Senior AI/ML Engineer specializing in GenAI agents and LLM workflows

San Francisco, CA6y exp

“LLM/AI engineer with production experience building a retrieval-based document intelligence system that extracts information from PDFs/emails, backed by Python + Spark pipelines. Focused on reliability and cost/latency optimization (caching, batch processing) and has hands-on orchestration experience with Airflow (sensors, retries, alerts). Also partnered with business stakeholders to deliver customer feedback classification/summarization for faster sentiment insights.”

Amit Sharma

Screened

Principal Software Engineer specializing in AI/LLM platforms, payments, and healthcare systems

San Francisco, CA25y exp

“Engineering player-coach who recently shipped an agent-based workflow to extract key info from unstructured web data (browser agents + CDP) and populate daily digests/calendars, owning architecture through testing. Also built a Flask-based LLM evaluation and regression testing system using G-Eval/Confident AI dashboards, and applies a rigorous, research-driven approach to selecting third-party tools with stakeholder buy-in; has healthcare ops/onboarding workflow experience at Vivio Health.”

Angie Fathalla

Screened

Mid-level Technical Consultant specializing in cloud infrastructure and enterprise automation

Clinton, NJ7y exp

“AI/LLM engineer focused on production-grade agent systems in high-stakes workflows, including a tax modernization initiative that automated tax form generation for 50,000 users. Demonstrates strong depth in reliability engineering, evaluation loops, and safe orchestration, with quantified improvements including pass-through gains from 62% to 94%, 30% lower token cost, and accuracy improvement from 88% to 99%.”

“Built and owned end-to-end production systems for a healthcare platform, including a predictive task recommendation feature (React + FastAPI + ML on AWS ECS) that cut backlog 20% and saved coordinators ~10 hours/week. Also productionized an AI-native RAG system (vector DB + LLM) delivering 40% faster query resolution, and led phased modernization of a monolithic FastAPI service into async microservices using feature flags and canary releases.”

Sai Karthik Chittamuru

Screened

Senior Salesforce Developer specializing in AI systems and enterprise cloud solutions

Pittsburgh, PA15y exp

“Salesforce-focused engineer with hands-on experience building Sales Cloud and Service Cloud solutions, including a Zoho billing integration for quote/contract workflows and a multi-panel LWC case management dashboard. Stands out for making practical architecture decisions around middleware vs. custom REST, handling idempotency with upsert patterns, and modernizing legacy Aura patterns with Lightning Message Service.”

“Built a production B2C behavioral interview system for job seekers using LangGraph/LangChain on AWS Bedrock with Nova models, plus a FastAPI backend and Vercel AI SDK frontend. Stands out for practical agent reliability work: local stress testing, OpenTelemetry-to-Datadog observability, token/cost monitoring, and guardrails to keep conversations on track and resistant to instruction override.”

“Built production-grade Python systems in a medical/imaging context, including an image feature extraction and survival prediction microservice with strong testing, validation, and observability practices. Also developed a Playwright-based autonomous job application agent that handled dynamic UIs and anti-bot challenges with stealth tooling, proxies, and human-in-the-loop escalation.”

Akhil Kunala

Screened

Mid-level Software Engineer specializing in backend systems and cloud-native FinTech

Seattle, WA5y exp

“Amazon engineer with 5+ years of experience who built an AI-assisted log investigation and triage workflow that cut debugging time by about 30% during on-call incidents. Combines observability tooling like CloudWatch and Splunk with Python, prompt engineering, and RAG-based diagnostics, and has practical experience orchestrating agentic AI workflows with a strong human-in-the-loop reliability focus.”

Prakash Bhanu

Screened

Director of Software Engineering specializing in cloud, platform, and FinTech systems

Sunnyvale, CA22y exp

“Senior software engineering leader with broad 0-to-1 product experience spanning web apps, microservices, monoliths, messaging platforms, ML/AI products, and large-scale distributed systems. Notable examples include building a payroll/finance product for cast and crew, a distributed messaging platform, and a Walmart application deployed across multiple CDNs and clouds handling hundreds of TPS, with personal ownership across architecture, design, coding, and support.”

“Backend-focused engineer with experience at AWS building a global alarm processing platform (Python, Lambda/SQS/DynamoDB) handling traffic spikes and reliability issues; resolved duplicate alerts and latency under load by fixing hot partitions and enforcing idempotency. Previously at Cognizant, built Java/PostgreSQL backend workflows for healthcare dashboards using pre-aggregated summary tables, strong SQL optimization, and state-driven job orchestration with ELK-based observability and production guardrails.”

Srinivas Vasudevan

Screened

Junior Software Engineer specializing in distributed systems and FinTech

Durham, NC3y exp

“Built an end-to-end payment fraud monitoring dashboard with a React/TypeScript frontend, GraphQL backend, Redis hot path, and a production RAG chatbot, while solving real-time latency and scaling issues. Also shipped an OCR system on AWS EKS for a live manufacturing line at Troxler, improving production accuracy by 15% with custom preprocessing and model tuning.”

“Senior product leader with a track record of transforming legacy and labor-intensive products into AI-native, high-growth platforms across automotive SaaS, legal tech, enterprise software, and UCaaS. Most notably, they rebuilt CallRevu’s call analysis engine to replace human review with AI, cutting processing costs by 93% and reducing turnaround from 30 minutes to under 3 seconds, while also launching a new adjacent product line.”

“Backend-focused AI engineer with enterprise experience building startup-style internal products at JPMorgan Chase. He helped create an AI-powered financial research platform for analysts, leading retrieval and multi-agent orchestration work that cut research prep from hours to under 20 minutes while scaling across large volumes of SEC filings and earnings transcripts.”

Sanjay Santhanam

Screened

Mid-level AI Software Engineer specializing in LLMs and FinTech data systems

San Jose, CA4y exp

“Backend/AI systems engineer focused on productionizing agentic document-processing workflows for large financial PDFs. They describe owning deployments end-to-end, combining Python, Redis, LLM function calling, RAG/ReAct-style orchestration, and strong reliability practices to deliver 80% faster processing, reduce parsing errors from 12% to ~1%, and sustain 99.9% uptime in high-concurrency environments.”

“Built and productionized an LLM-powered clinical assistant at a healthcare startup, re-architecting a prototype into a robust RAG system on AWS with guardrails, citations, monitoring, and automated tests for clinical reliability. Works closely with clinicians to convert workflow feedback into evaluation criteria and iterative system improvements, and has hands-on experience debugging agentic systems in real time (including during live client demos).”

“Backend engineer who built and evolved an internal multi-agent AI research platform (Electron + FastAPI) integrating OpenAI, focused on fast, reproducible experimentation with strong observability and run metadata for debugging. Has led incremental backend refactors with feature flags and parallel validation, and brings production-grade access control expertise from ServiceNow (table/field ACLs and row-level-style enforcement).”

“Backend engineer focused on scalable, security-first platform architecture—recently built an end-to-end centralized access-control system that launched successfully with ~50k early adopters and was designed to support ~10x traffic growth. Experienced in production authn/authz (token verification, handoff/session migration), and in de-risking migrations via feature flags, phased rollouts, A/B testing, and Splunk-based monitoring.”

“Backend engineer with hands-on experience building Flask REST APIs (auth, CRUD, S3 media uploads) and driving measurable Postgres/SQLAlchemy performance gains (p95 reduced to 200–400ms by eliminating N+1s and switching to keyset pagination). Implemented multi-tenant isolation with strict tenant scoping plus Postgres RLS, and built an OpenAI-powered quiz generation pipeline using queued workers, structured JSON outputs, and Celery/Redis optimizations to stabilize high-throughput workloads.”

“CMU candidate with hands-on experience taking LLM concepts from research prototypes toward production-ready designs (structured outputs, guardrails, failure-scenario evaluation). Also partnered with sales/customer teams at Mazecare to drive adoption with Dontia Alliance (largest dental clinic chain in Singapore) and engaged Singapore government stakeholders, bridging clinical workflow needs with IT security/integration concerns.”