Pre-screened and vetted.
Mid-level Software Engineer specializing in full-stack web and AI systems
“Full-stack and AI systems engineer who has shipped both enterprise fintech and real-time voice AI products. At NCR, they repaired a broken transaction-fee workflow end to end using React/TypeScript, Lambda, and DynamoDB; at Lillup, they turned a research voice prototype into production infrastructure, cutting latency from 350ms to under 200ms and raising user ratings from 2.8 to 4.1. They also built an LLM side project that uses Claude and GPT to cross-review each other through structured JSON consensus rounds.”
Senior Full-Stack Engineer specializing in frontend and healthcare platforms
“Frontend engineer with experience modernizing a large healthcare platform from Adobe Flex to React/TypeScript using micro frontends while keeping legacy systems live during migration. Brings strong performance tuning skills for data-heavy UIs and real-time map applications, including profiling-driven React optimization, Next.js SSR, and WebSocket-based live tracking.”
Senior Full-Stack Software Engineer specializing in SaaS platforms on AWS
“Full-stack engineer with strong DevOps/AWS experience who ships end-to-end React/TypeScript + Node/Python systems and operates them in production. Built an LLM-assisted recommendations workflow for a SaaS product with robust reliability controls (schema-validated JSON outputs, fallbacks, caching, monitoring) and measured impact via adoption, time saved, and override rates; also experienced delivering MVPs fast in early-stage startup ambiguity.”
Junior Full-Stack Software Engineer specializing in automation and web development
“Built Meet.AI end-to-end and made concrete architecture/performance decisions (RPC with type-safe integration; SSR + query prefetching for instant data display). Also created a Python tool at Abbott to resynchronize Ansible inventories and eliminate manual intervention by scheduling it in a Jenkins pipeline; has hands-on Docker/microservices experience including serving a pretrained LLM.”
Junior AI Engineer & Full-Stack Developer specializing in AI agents and RAG systems
“Full-stack TypeScript/React/Next.js builder who created an end-to-end customer-facing product (AI Job Master) that generates personalized outreach from resumes and job descriptions. Demonstrates strong product + engineering ownership with rapid MVP iteration, instrumentation-driven prioritization, and pragmatic reliability patterns (microservices, queues, correlation IDs, retries) while tackling a key AI challenge: user trust and output consistency.”
Intern Software Engineer specializing in full-stack development and IAM automation
“Built and owned a Python/FastAPI backend for a custom translation service used in a showroom application, integrating DynamoDB and connecting the service to a SPA/Next.js frontend. Has exposure to Kubernetes-based deployments and GitHub Actions CI/CD, and contributed to planning an on-prem to cloud/SaaS migration at Sherwin-Williams by gathering requirements across multiple plants/factories.”
Mid-Level AI Engineer & Product Builder specializing in LLM agents and real-time apps
“Cloud/distributed-systems engineer who has shipped real-time, offline-capable ledger/expense infrastructure and solved tricky cross-layer production bugs (carrier handoff retries causing duplicate writes) using packet captures and device logs. Also built modular Python ETL/catalog pipelines for e-commerce with config-toggled plugins for customer-specific pricing/SKU rules, and iterated product changes directly with on-site fulfillment operators using feature flags.”
Mid-level Full-Stack Software Engineer specializing in cloud, data pipelines, and GenAI
“Full-stack engineer currently building an employee management system end-to-end with React, Node/Express, and PostgreSQL, including JWT auth and RBAC. Previously worked at TCS on large-scale State Bank of India web applications, applying Redis caching, server-side pagination/filtering, and async job offloading to improve performance and reliability.”
Mid-level Software Engineer specializing in backend engineering and applied AI workflows
“Backend engineer with fintech/transaction-processing experience who built and optimized a Spring Boot + PostgreSQL + AWS service handling money transactions, resolving peak-traffic latency via query/index and connection pool tuning. Shipped an LLM-driven risk-flagging workflow integrated via a FastAPI Python service, owning prompt design, validation guardrails, monitoring, and human-in-the-loop escalation to reduce false positives and improve precision over time.”
Mid-Level Full-Stack Developer specializing in React, React Native, and cloud data systems
“Full-stack engineer who built a checklist configuration/task execution system using Next.js App Router + TypeScript, with a React Native app consuming the execution UI via WebView. Was the only full-stack developer at a very small startup (CTO/CFO/CEO team), owning feature delivery plus client-facing on-call debugging, and has hands-on Postgres modeling and query optimization experience.”
Entry AI Engineer specializing in LLM agents, RAG, and computer vision
“Robotics/AV-focused candidate who contributed to an F1TENTH autonomous vehicle college project, building key autonomy components from raw sensor data to driving commands. Strong in perception and state estimation (visual odometry, particle-filter localization), plus mapping (occupancy grids) and planning/control (RRT, Gap Follow, PID), with hands-on ROS tooling and simulation validation in Gazebo/RViz and ROS environment containerization using Docker.”
Mid-Level Backend Software Engineer specializing in scalable cloud systems and LLM automation
“JavaScript engineer with open-source experience on a database visualization library, focused on real-time rendering performance for large datasets (virtualized DOM rendering, requestAnimationFrame/debouncing, memoization) and on raising project quality via tests and CI performance benchmarks. Also built Kafka-based messaging documentation and sample producer/consumer apps to speed onboarding, and has experience diagnosing production issues including concurrency-related duplicate data problems.”
Junior Full-Stack Developer specializing in React/Next.js, Node.js, and AWS
“Led an end-to-end build of bhangrascape.ca, making key architecture choices across Next.js/Node/Postgres on AWS and implementing S3-based media storage with presigned URLs. Strong focus on quality and reliability via Zod validation, Jest tests, Postman endpoint testing, and CI/CD with GitHub Actions, plus hands-on UX ownership from Figma prototyping through reusable React components and A/B testing.”
Senior Full-Stack Engineer specializing in AI-powered web products
“Backend/data engineer who has built production AI video generation services on AWS using a hybrid serverless + container architecture (FastAPI, Lambda, ECS, Postgres/Redis) with strong reliability practices (auth, retries/timeouts, structured logging, CloudWatch + Slack alerting). Also delivered AWS Glue ETL pipelines with schema evolution handling and modernized a legacy SAS healthcare reporting workflow to Python with parity validation and parallel-run migration.”
Mid-Level Software Engineer specializing in LLM applications, RAG, and OCR automation
“At Trellis, built and shipped a production multi-agent, authenticated GenAI chatbot for sensitive financial account inquiries (loan/payment lookups), using dynamic model routing to control latency and cost while improving accuracy. Implemented prompt-injection defenses (Meta Prompt Guard), RAG with LangChain, and LLM-as-a-judge evaluation; the system cut manual support call volume by 40%+ and was refined through close collaboration with QA-driven user testing.”
Director-level Head of Technology specializing in e-commerce platforms and digital transformation
“B2B product builder with prior experience taking products from 0-1 and scaling to revenue; previously implemented e-commerce search and turned it into a monetized paid-results/bidding platform requiring architectural changes and GTM alignment. Now exploring a startup idea focused on retention and upsell for B2B companies, targeting the underserved long-tail partner segment and already validating the gap with industry leaders and POC conversations.”
Mid-Level Full-Stack Product Engineer specializing in TypeScript and React
“Software engineer and co-founder with 0-to-1 SaaS experience who built and owned an end-to-end reporting/analytics dashboard on Next.js App Router + TypeScript, including Postgres schema design, aggregation query optimization, and post-launch performance/monitoring. Has delivered measurable React dashboard performance gains (~35% improvement in time-to-insight) and built durable, idempotent job/state-machine workflows using serverless functions and Postgres.”
Mid-Level Software Engineer specializing in distributed systems and cloud microservices
“Built and productionized a RAG-based semantic search system for video-derived data, focusing on measurable success metrics (p95 latency, reliability, cost/request) and strong observability (prompt versions, retrieved docs, tool calls, token usage). Experienced in diagnosing real-time issues in LLM/agentic workflows and in supporting go-to-market efforts through tailored technical demos, rapid POCs, and post-close onboarding.”
Intern Machine Learning Engineer specializing in deep learning and LLM systems
“Built and shipped a personal LLM-powered news aggregation platform (Clear Brief) that scrapes ~200 articles per cycle, clusters them into ~15–30 consolidated stories, and supports on-demand deep dives via a Next.js API route. Emphasizes production-minded reliability (token/cost controls, timeouts, graceful frontend degradation) and database-backed orchestration using SQLite with retry + exponential backoff for burst processing.”
Entry-level Full-Stack Engineer specializing in AI and distributed systems
“Full-stack engineer who built an AI-based inventory/procurement query system at Botlily/Botlerly using Flask and Google Sheets as a live knowledge base, overcoming Sheets latency with caching and structured in-memory models. Demonstrated strong LLM product engineering (40% accuracy improvement via preprocessing/prompting) and customer-driven iteration with bar/restaurant owners, evolving the tool into a more comprehensive inventory management and forecasting solution.”
Intern Software Engineer specializing in full-stack web and game systems
“Built a production 13-step LLM agent pipeline at Sentari AI that converts diary entries into personalized AI responses and a persistent structured user profile. Stands out for a pragmatic approach to production AI: strict schemas, function calling, state-machine orchestration, confidence thresholds, logging, and validation layers to control non-determinism and prevent bad profile updates.”
Executive technology leader specializing in AI, cloud architecture, and FinTech platforms
“Bootstrapped founder of FAMRO LLC with 15+ years spanning startups and corporate roles, including COO experience at an AI/ML startup that built a retail marketing analytics product using camera feeds. Also worked on a clean-tech venture, EnerIO, which won 1st position from Pakistan and was invited to pitch at the GCIP/GEF event in San Francisco in 2015.”
Junior AI Engineer specializing in machine learning systems
“Engineer with hands-on experience building adaptive assessment and LMS-style platforms across React/TypeScript, edge/serverless backends, and Postgres, with strong evidence of cross-layer debugging and performance optimization. Also brings ML product experience from a small-team internship, where they shipped a CatBoost-powered investor demo under ambiguity and created reusable inference infrastructure.”
Junior Software Engineer specializing in AI and full-stack development
“Junior web developer turned applied AI builder who has shipped both user-facing web UX improvements (Vue.js + Drupal/Twig) and production LLM systems. Built a Google Cloud-hosted Llama/Ollama RAG customer-service chatbot with citation-based guardrails and a metrics-driven eval loop, and also delivered a large-scale Python pipeline analyzing 14M Amazon consumer reviews for flavor-trend detection.”