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Vetted TypeScript Professionals
Pre-screened and vetted.
SOURABH MISHRA
Senior Software Engineer specializing in FinTech and distributed systems
“Backend/AI engineer who has built a rule-service platform on AWS and evolved it into an agentic RAG system using LangChain, ReAct, tool calling, and LLM-as-judge review. Notable for combining heavy AI-assisted development with production safeguards like manual CR, CloudWatch monitoring, fallback strategies, benchmark testing, and user-feedback-driven model improvement.”
Qianfan Luo
Junior Software Engineer specializing in backend systems and AI/ML pipelines
“Robotics-focused engineer with ROS 2 experience who has built and debugged real-time, distributed control/orchestration systems under production-like latency and safety constraints. Led platform changes at Persona for a real-time verification orchestration system using deterministic state machines and async workers, and has hands-on experience stabilizing multi-robot navigation/SLAM behavior using rosbag, RViz, and stress testing in simulation (Gazebo).”
Jolie Qiu
Mid-Level Software Engineer specializing in AWS data infrastructure and pipeline automation
“AWS-focused software engineer who built a self-serve ETL pipeline scheduling service for non-engineers, including automated CloudFormation-based onboarding that cut setup time from 2–3 weeks to ~5 minutes. Strong in production reliability and customer-facing data platforms (EMR/DynamoDB/Lambda), with examples spanning pagination at scale, cross-table consistency, and phased rollouts to improve Parquet log SLAs.”
Bhavani Shekhawat
Engineering Manager specializing in AI/ML platforms and 0→1 product delivery
“Player-coach engineer/lead on a high-scale research integrity platform ("Lighthouse") that flags fraud/manipulation signals across ~3M academic manuscripts per year. Owns architecture decisions (ADRs), implements across Go/Java/React services, and introduced NLP (SciBERT embeddings + human-in-the-loop) to assess out-of-context citations while also handling production incidents with a data-consistency-first approach.”
Rashi Agrawal
Mid-Level Full-Stack Software Engineer specializing in distributed systems and cloud-native microservices
“Backend engineer (4 years) who built an end-to-end Python backend for a patent-pending in-car massager/heater system, including GraphQL data modeling and Bluetooth integration with an ESP32 microcontroller (reverse engineered a niche protocol). Also has strong platform experience: on-prem Kubernetes/CI-CD (Jenkins/GitLab, exploring ArgoCD GitOps), Terraform-based infra workflows, a RabbitMQ messaging library used across microservices, and an on-prem migration of ~30 critical applications with rollback/parallel-run strategy.”
Yuan-Hsuan Wen
Intern Software Engineer specializing in AI agents, RAG pipelines, and semiconductor systems
“Built a web-based interface that connects an internal bug system to an LLM for initial debugging and issue classification, aiming to boost QA and software engineer efficiency while balancing latency and accuracy. Worked as a one-person project and managed constraints like limited hardware and difficulty extracting team debugging context, relying on manager communication and rapid modeling to validate direction.”
Christopher Bun
Executive AI/ML technology leader specializing in healthcare, biotech, and legal AI
“Repeat founder and startup advisor with experience spanning academic, health tech, legal tech, sports, and gaming. Has participated in fundraising and due diligence and has built companies, engineering teams, and software platforms from scratch, with a strong product-design-first approach to product-market fit and market selection.”
Edmund Chan
Mid-level Frontend Engineer specializing in web platforms and internationalization
“Frontend engineer with significant ownership of Bloomberg's Japanese regional platform, building a complex multi-app Next.js experience for retail investors and financial professionals. Stands out for combining high-scale localization architecture, advanced TypeScript/component-system design, and measurable UX performance wins in demanding financial products.”
Arun Ganesh
Junior Software Engineer specializing in healthcare AI and cloud infrastructure
“Amazon Health AI engineer who has owned both full-stack clinical product features and production LLM systems end to end. Built HIPAA-compliant GraphQL and agentic RAG architectures for provider workflows across 125,000+ patients, with measurable impact including 30% higher clinical relevance, 55% lower lookup time, and 12% less false medical information.”
“Full-stack engineer at Vanguard who architected and shipped a production AI onboarding chatbot using React, Python, LangChain, RAG, and AWS Bedrock, reaching 50,000+ prospects in two months and reducing drop-off by 26%. Particularly compelling for teams building regulated AI products: they combine hands-on full-stack delivery with guardrails, observability, and experimentation, and also build consumer AI products on the side in endurance coaching.”
Chester Nielsen
Executive Chief of Staff and Strategic Operations Leader across SaaS, government, and national security
“Entrepreneurial consultant who relocated to Boston to build a practice from scratch through intensive networking and pro-bono work, leading to being listed as a trusted provider in Leader Bank's CEO toolbox and generating qualified leads. Uses structured strategic frameworks (OODA, Porter's Five Forces, SWOT) to evaluate risk, resource lift, and enterprise/customer impact, with a strong ownership-and-accountability orientation.”
LuYao Chen
Junior Software/ML Engineer specializing in AI systems, cloud infrastructure, and applied research
“Backend/infra-focused engineer with experience spanning Go-based MCP servers for an AI-assisted Kubernetes on-call diagnosis chatbot and a Python/Flask PagerDuty automation integration. Previously at Tesla, optimized high-volume battery test data in PostgreSQL using JSONB, partitioning, and a timestamp normalization pipeline; also built PyTorch PINN training workflows and achieved a 20x speedup via batch vectorization.”
Nishitha Thummala
Mid-level AI/ML Engineer specializing in LLMs, RAG, and scalable inference
“Backend/retrieval-focused engineer with production experience at Perplexity building a large-scale real-time Q&A system using retrieval-augmented generation, emphasizing low-latency, high-quality answers through ranking, context optimization, and caching. Also has orchestration experience from both product-facing LLM pipelines and large-scale infrastructure workflows at Meta, and has partnered with non-technical stakeholders to align AI trade-offs with business goals.”
Kowshika M
Mid-level AI/ML Engineer specializing in LLM fine-tuning, inference optimization, and AI safety
“AI/LLM engineer with production experience at NVIDIA, where they fine-tuned and deployed a financial-services chatbot and cut latency ~50% using TensorRT + NVIDIA Triton, scaling via Docker/Kubernetes. Also has consulting experience at Accenture delivering a predictive maintenance solution for a logistics network, bridging non-technical stakeholders with actionable dashboards.”
Sahil Sinha
Mid-Level Software Engineer specializing in full-stack development, cloud, and data infrastructure
“Software engineer at Fannie Mae (~3 years) working on high-volume loan data pipelines using AWS (SQS/S3), Java listeners, Postgres, and Python/SQL-based data quality validation. Also built a chess data collection system (leveraging experience as an International Master) with robust retry/monitoring, schema-change handling, and idempotent backfills to prevent bad data from reaching downstream systems.”
Geetika Jain
Mid-Level Software Engineer specializing in Azure AI and full-stack development
“Hands-on AI/LLM engineer who built a RAG-based product feature end-to-end, including prompt engineering, safety guardrails, and an automated adversarial + load-testing harness. Diagnosed real production issues (null responses) via Azure logs/metrics and drove an architectural fix by separating model deployments to address token/quota limits. Also runs internal developer enablement through short theory-to-hands-on AI workshops after completing a Microsoft AI certification.”
Joseph Fusco
Senior Software Engineer specializing in AI-powered developer tooling and backend platforms
“Backend/product engineer from Postman Flows who has owned complex platform features end-to-end, including production versioning and an LLM-powered flow-building orchestration layer. Stands out for combining product-minded backend design, agentic AI workflow implementation, and strong production reliability work, including re-architecting a failing event pipeline from in-memory to managed queues.”
Dilpreet Singh
Executive CTO and Founder specializing in AI platforms and hyper-scale SaaS
“CTO-minded builder seeking to join a startup; previously created an AI-driven platform that abstracted away DevOps and infrastructure for drug discovery researchers. Emphasizes high-leverage, zero-to-one execution with managed cloud/open-source tooling, and a strong reliability/reproducibility mindset validated against existing scientific pipelines.”
“Backend/full-stack engineer (Amazon experience) who built an AWS-based integration testing platform using Flask, ECS, Docker, and CloudWatch—cutting 1000+ test cases from ~5 hours to ~30 minutes while improving log visibility for non-engineering users. Also led a zero-downtime EU region migration with rigorous ORR testing, and built a Kinesis/Firehose/S3 + Glue/Spark replay mechanism for resilient data recovery. Side project: reproducible, cost-efficient LLM hosting platform on EKS using CDK and Karpenter for scale-to-zero.”
Nikhil Reddy
Mid-level AI/ML Engineer specializing in GPU inference and LLM platforms
“Built and deployed an LLM-powered platform that turns models into scalable REST/gRPC APIs, focusing on keeping GPU-backed inference fast and stable during traffic spikes. Experienced with AWS orchestration (EKS/ECS/Step Functions), safe model rollouts, and production-grade monitoring/testing for reliable AI agents and workflows.”
Alfred Dwan
Intern Software Engineer specializing in AI, cloud-native systems, and MLOps
“Backend/full-stack engineer who has owned a production recruiting platform end-to-end (TypeScript/Node microservices for scraping/cleaning/serving job data, RabbitMQ for spike handling, MongoDB + Elasticsearch, AWS containers) with pragmatic CI, logging/alerts, and Docker Compose E2E tests. Also operated high-traffic event pipelines during a Binance internship using Kafka + Redis idempotency, with strong observability and failure-mode/rollback/degradation practices, and has experience designing developer-friendly REST APIs and resilient browser automation for E2E flows.”
Christian Alcala
Mid-level Software Engineer specializing in LLM-powered analytics
“Engineer with a pragmatic, production-focused approach to AI development, emphasizing verification, observability, and system design over hype. Built LLM-driven features and automated regression/validation pipelines, including quality measurement work at Oracle, and uses hands-on projects to test how AI fits into real business workflows.”
Graham Lutz
Director of Engineering specializing in platform, AI, and cloud-native SaaS
Dinesh Mishra
Executive AI Product Leader specializing in FinTech and agentic AI platforms
“Fintech/neobank CTO (5+ years across US and UK markets) now building Payzo Money, a fintech copilot for SMBs covering expenses, accounting, invoicing, and payroll. Pre-revenue and seeking a $5M seed round, with active Bay Area conversations and a clear focus on bank sponsorship plus compliance/operations readiness; leverages Claude-based AI agents to accelerate building with limited resources.”