Vetted TypeScript Professionals

“Full-stack engineer with startup experience at sub-100-person companies, owning major product and platform changes across Go, React/TypeScript, Python, Postgres, and SQL Server. Stands out for redesigning a core repository-like workflow component without breaking existing customer data and for shipping operational tooling at Tovala that saved teams 15 hours of manual work per week.”

“Backend/data platform engineer who owned an enterprise Django REST + PostgreSQL reporting backend and built Python ETL pipelines to normalize 3M+ legacy customer records, improving data reliability by 85%. Strong Kubernetes/GitOps practitioner (Helm, ArgoCD, Jenkins/GitHub Actions) with real-world production debugging experience, plus Kafka streaming at 5M events/day and a zero-downtime monolith-to-event-driven microservices migration on AWS that cut infra costs by 42%.”

“Frontend engineer who led an end-to-end responsive enterprise banking platform in a regulated environment, emphasizing domain-based architecture, strict TypeScript contracts, and explicit state-machine-like flow modeling. Implemented Redux + React Query state separation, claimed 100% Jest coverage, and improved Jenkins CI/CD to speed deployments ~30% while also resolving major re-render performance bottlenecks.”

“Full-stack product engineer who has shipped customer-facing features end-to-end, including a product detail page backed by Java/Spring Boot microservices and a React/TypeScript UI. Demonstrated measurable impact through performance and maintainability improvements (30% faster APIs, 25% less duplicated UI code, 40% reduced API complexity via GraphQL) and has operated/scaled apps on AWS with CI/CD, monitoring, and incident-driven scaling fixes.”

“Full-stack engineer who built a live-streaming edtech platform at KratosIQ, owning the entire frontend and the backend streaming layer. Notably migrated the system from a P2P mesh to an SFU architecture to handle scaling under heavy load, and delivered measurable React performance gains (450ms to 40ms render time) validated via Lighthouse and web vitals.”

Sai Kumar K

Screened

Mid-Level Frontend Engineer specializing in legal data platforms

5y exp

“Built and operated end-to-end legal-document data pipelines fed by hundreds of scraper sources, emphasizing data quality validation, reliability (CloudWatch monitoring/alerting, retries, backfills), and serving enriched legal data via serverless AWS APIs (Lambda/API Gateway). Experienced in keeping API contracts stable with additive versioning practices and shipping MVPs quickly with CI/CD and observability in place.”

Tarun Gowda

Screened

Mid-level AI Engineer specializing in Generative AI and multimodal RAG

Morristown, NJ3y exp

“Full-stack engineer who helped build and launch an internal genAI platform called GAIL, supporting multiple LLMs, confidential document upload for RAG pipelines, and collaborative chat. Worked across FastAPI, React/TypeScript, AWS/DynamoDB, and Azure, with notable ownership of backend RAG logic, MCP integration architecture, and frontend fixes that improved chat usability.”

“Lead developer on a Warner Brothers Discovery media management platform, building Python/Flask APIs and AWS-based workflows. Delivered a serverless search overhaul (Lambda + API Gateway + OpenSearch Serverless) while maintaining parity with legacy Rekognition tag-based search, and implemented event-driven ETL (SNS/SQS) to ingest/validate CSV metadata into PostgreSQL with strong logging and incident response practices.”

“Robotics software engineer focused on backend/integration for indoor autonomous mobile robots, with hands-on ROS 2 experience integrating Nav2/AMCL/TF2 and LiDAR/camera pipelines. Emphasizes production readiness—robust failure recovery, QoS-tuned distributed communication, and strong observability (logging/health checks)—validated through Gazebo simulation, sensor-data replay debugging, and Docker-based CI/CD deployment.”

“LLM/agentic systems builder who has deployed production solutions for a resource management firm, using an MCP-driven architecture with Neo4j + Elasticsearch and a ChatGPT frontend to generate candidate/company “SmartPacks” and answer entity Q&A. Also built a LangGraph/LangSmith-orchestrated multi-agent workflow that automates data-infra change requests end-to-end (impact analysis, SQL + tests, and PR creation), and delivered a ~60% latency reduction through TTL-based context caching while improving accuracy via a business data dictionary.”

“Backend engineer with Paycom experience who deployed a TypeScript web app on AWS and is re-architecting Stripe webhook handling using Kafka for durable, high-throughput asynchronous processing. Also delivered a freelance Python solution for a hospital that ingested sensor API data, normalized inconsistent readings, generated reports, and sent threshold-based email alerts while collaborating directly with hospital staff.”

Thanuja Mudududla

Screened

Mid-level Software Engineer specializing in full-stack cloud and agentic AI systems

San Jose, CA3y exp

“Backend engineer with hands-on ownership of production systems across maritime tracking, HR tech, and AI-powered document workflows. They combine strong operational instincts with measurable impact—cutting API latency from 10s to 3s, improving query performance by 60%, reducing deployment time by 50%, and driving 70% infrastructure cost savings with serverless design.”

Sreevalli Santhavel

Screened

Director-level AI Product Manager specializing in GenAI, LLMs, and SaaS platforms

Texas, USA12y exp

“Technical Product/Program Manager with architect-level involvement who leads customer-facing product builds from sales discovery and Figma design through engineering estimation, schema decisions, and cloud deployment. Has shipped integrated ecommerce and auction products, including vehicle inventory workflows tied to Salesforce, Stripe, and QuickBooks, and has applied AI/ML to warehouse QA, defect detection, and pricing recommendations.”

“Built and deployed a production, multi-tenant modular agentic AI platform at Easybee AI, using LangChain/LangGraph with Redis-backed durable state to make agents reusable, traceable, and auditable. Emphasizes reliability via strict tool schemas, deterministic controllers, tenant-level policy enforcement, and regression testing derived from real production failures; also delivered AI automation for legal/finance workflows (attorney draw and expense automation) with explainable, deterministic payouts.”

“Backend engineer who owned and shipped a campaign analytics API (FastAPI/Postgres/Redis/Celery) with ingestion from Instagram/YouTube, JWT auth, tests, and Docker deployment; improved performance from >1s to <150ms using precomputed aggregates and composite indexes. Experienced with Kubernetes GitOps using GitHub Actions + ArgoCD (zero-downtime rollouts, one-click rollbacks), Prometheus/Grafana observability, hybrid cloud-to-on-prem migrations, and real-time notification streaming via Redis Pub/Sub + WebSockets.”

“Candidate is actively exploring AI-driven development and modern coding assistants like Claude AI, Cursor, Gemini, and other LLM-based tools. While they have not yet led AI-agent projects or used multi-agent systems in production, they are proactively building knowledge through AI coursework and the Microsoft AI Engineering specialization.”

Ashutosh Srivastava

Screened

Senior Engineering Manager specializing in AI platforms and cloud-native backend systems

Sunnyvale, CA11y exp

“Player-coach engineering leader who stayed hands-on (coding/reviews) while leading delivery, including designing an event-driven AI workflow engine with explicit state modeling and robust retries. Built near real-time enterprise analytics for campaign measurement and drove reliability/process improvements (observability, incident runbooks, release management). Introduced lightweight CI/CD and automated testing to cut release time by ~40% while maintaining quality.”