Pre-screened and vetted.
Mid-level Backend Engineer specializing in Python APIs and cloud-native services
“Data engineer with experience at Morgan Stanley and Star Health owning production-grade lakehouse pipelines for credit risk and healthcare datasets. Built Azure/Databricks/Delta/Snowflake-based platforms processing millions of records per day with strong data quality, observability (Monte Carlo/Azure Monitor), and reliability practices, plus experience delivering curated data services with performance tuning and backward-compatible versioning.”
Mid-level Full-Stack Software Engineer specializing in AI-enabled web apps and data platforms
“Software engineer who built an AI marketing/outreach agent end-to-end: Next.js (App Router + TypeScript) frontend integrated with a Python/Django REST backend using LLMs (Gemini, ChatGPT-4o) and SQL databases. Demonstrated measurable performance wins—improved a 100k-record UI by 15% (Lighthouse) and cut a Postgres-backed search API from ~3s to ~1ms via indexing—while also owning post-launch monitoring (webhooks/cron, New Relic/CloudWatch) and customer support.”
Junior Backend/Cloud Software Engineer specializing in microservices and cost-optimized AWS systems
“Built a production anomaly-detection workflow at VDOIT for messy cloud billing/cost data, emphasizing validation, idempotency, retries, and monitoring. Delivered measurable impact by preventing ~$50K/month in overspend and improving response time, and is now applying the same multi-step pipeline approach to LLM-based agent workflows.”
Mid-level Software Engineer specializing in data pipelines, web scraping, and APIs
“Backend/data engineer who has owned end-to-end production pipelines and data services, processing ~500K–1M records/day from APIs/logs into MySQL and serving via REST APIs. Strong focus on reliability and data quality (ELK + structured logging/monitoring), with measurable improvements (~30% reduction in bad data, ~20% query performance gains) and experience operating external data collection/scraping systems with anti-bot and schema-change resilience.”
Senior Full-Stack Software Engineer specializing in cloud-native web, mobile, and AI features
“Frontend lead for a consumer-facing social platform, owning architecture through release. Built scalable React/TypeScript systems (Redux Toolkit, Remix) with a shared Storybook component library and strong quality gates (CI, Jest/Cypress). Experienced modernizing legacy codebases incrementally with feature flags and shipping major dashboard features with staged rollouts and close QA collaboration.”
Senior Full-Stack Software Engineer specializing in Ruby on Rails and React
“Frontend engineer with React/TypeScript experience who has led end-to-end UI work on a fintech product (React frontend with NestJS APIs), emphasizing performance (virtualized rendering, memoization, lazy loading, profiling) and quality at scale (unit tests and TDD). Also built and iterated on a snooker sports app, simplifying UX through audience-focused design decisions and streamlined onboarding.”
Junior AI/ML Software Engineer specializing in Generative AI and scalable data pipelines
“Built and operated large-scale biodiversity/ecological research platforms, integrating 50+ heterogeneous global datasets into a unified BIEN 3 schema on PostgreSQL/PostGIS and improving data consistency by 35%. Strong production engineering background (Linux monitoring, CI/CD performance gates, Docker on AWS/Azure) plus applied AI work building a Python RAG system (0.90 precision) and halving latency with Elasticsearch.”
Junior AI Engineer specializing in LLM evaluation, prompt engineering, and AI orchestration
“LLM workflow builder who has deployed a personalized GPT experience (including Delphi AI-based knowledge ingestion) and built a LangChain/LangGraph job-aggregation pipeline that ingests, normalizes/dedupes, filters, then uses an LLM to rank and summarize matches. Emphasizes production reliability with structured outputs, retries/fallbacks, metric-driven evaluation, logging/prompt versioning, and A/B testing, and collaborates with non-technical stakeholders through demo-driven iteration.”
Junior Full-Stack Developer specializing in React Native and Java/Spring
“Frontend engineer who created an in-house React-like framework (“React-Wilcox”) enabling modern, event-driven UI components on extremely legacy browsers (as far back as 2002), including race-condition avoidance via batched state updates. Also does freelance work untangling AI/vibe-coded frontends for nontechnical founders, componentizing UIs and fixing routing/readability, and recently built a React+TS social app for martial artists with privacy-preserving location distance features.”
Junior Full-Stack Software Engineer specializing in React, Node.js, AWS, and Generative AI
“Built and production-deployed a Streamlit-based PDF RAG chatbot using LangChain (FAISS, embeddings, prompt templates) and OpenAI, optimizing Streamlit’s stateless behavior by caching vector DB + chat history to cut latency and API cost. Demonstrates a rigorous evaluation mindset (gold datasets, unit tests, LLM-as-judge, groundedness KPIs) and has experience communicating privacy/accuracy safeguards (RBAC, data masking, citations) to a non-technical client at Kalven Technologies.”
Senior Software Engineer specializing in full-stack systems, big data, and applied AI
“Built and deployed ForensicLLM, a local domain-specific LLaMA-3.1-8B model for digital forensic investigators using RAFT + RAG over 1000+ curated research papers, with citation-aware responses and rigorous evaluation (BERTScore/G-Eval). Deployed via vLLM and Docker and validated through a chatbot survey with 80+ participants; published at DFRWS EU 2025.”
Intern Machine Learning Engineer specializing in Generative AI and RAG systems
“Early-career AI/LLM builder who created and deployed a multi-agent news analysis agent (Patrakarita) using CrewAI, coordinating researcher/analyst roles to turn noisy article URLs into structured, prioritized outputs (claims, tone, verification questions, opposing views). Strong focus on orchestration debugging and reliability evaluation, including measuring hallucination/redundancy and improving reasoning by refactoring pipeline sequencing.”
Junior Full-Stack Software Engineer specializing in mobile, cloud, and GenAI integration
“Software engineering intern with hands-on ownership of a Java/Spring Boot order management microservice, including production performance tuning via Redis caching and database indexing driven by API logs/metrics. Also contributed to a production mobile-backend LLM feature using RAG with embeddings over structured data and documents (DB + object storage), with guardrails to keep responses grounded.”
Senior C++/Rendering Engineer specializing in game engines and GPU (CUDA) computing
“Gameplay/physics-focused C++/UE5 developer who builds end-to-end real-time 3D systems (custom melee hit reactions, animation, and terrain movement) and debugs deep rendering issues using GPU/pixel-shader tooling. Has hands-on experience with complex networked physics, including ragdoll replication with bandwidth compression and hybrid deterministic/non-deterministic prediction approaches, and is interested in realistic soccer/football movement systems.”
Junior Software Engineer specializing in full-stack web development and test automation
“Full-stack engineer who built and owned a production workflow/kanban-style drag-and-drop system in Next.js (App Router) with Postgres/Prisma, including reusable component abstractions, Cypress E2E coverage, and post-launch performance/bug ownership. Notable for measurable impact (25% faster UI dev, ~30% query perf improvement) and for leading an incremental Express→NestJS migration that reduced technical debt (~40%) through better structure, docs, and team enablement.”
Mid-level Python Full-Stack Engineer specializing in AI microservices and cloud data platforms
“Backend-leaning full-stack engineer in fintech/payments who shipped an end-to-end Stripe payments + webhook system for a financial microservices platform, emphasizing ledger accuracy via idempotency, transactional writes, retries, and DLQs. Also delivered a real-time React/TypeScript payment status dashboard informed by user interviews, and improved production performance by 35% p95 latency through PostgreSQL tuning and Redis caching on AWS.”
Junior Software Engineer specializing in backend, cloud, and robotics automation
“Graduate Research Assistant in Robotics at Arizona State University who built an end-to-end LLM-driven task execution framework enabling collaborative robots to convert high-level natural language instructions into safe, executable ROS actions. Implemented robust monitoring, failure detection, and automatic replanning, and addressed real-world issues like timestamp/frame-transform mismatches and heterogeneous robot interoperability using adapter nodes.”
Mid-level Sales Engineer specializing in GNSS/RTK and technical pre-sales
“GEODNET engineer specializing in edge-to-cloud, real-time GNSS data pipelines at global scale (thousands of heterogeneous base stations). Built deterministic-latency ingestion with RTCM/MSM normalization, jitter buffering, and firmware-aware parsing, and shipped production hotfixes using canary rollouts and deep observability. Also delivers customer-specific GNSS/RTK outputs via tested Python tooling (CLI/API) and collaborates on-site with operators to resolve firmware and network-driven issues.”
Mid-Level Software Developer specializing in .NET web applications on Azure
“Full-stack developer who built an end-to-end billing/allocation/payment and reporting system used daily by a major film-industry union, including queuing-based check assignment, admin auditing, data cleanup tools, and an external reports portal. Also delivered a factory production scheduling/analytics app for a lock manufacturer, and typically implements APIs in C#/.NET with DTO shaping and pub/sub messaging for microservices consistency.”
Junior Data/AI Engineer specializing in MLOps, real-time pipelines, and LLM applications
“Built an LLM-driven MLOps agent at SBD Technologies that automated an EV-charging prediction workflow end-to-end, integrating with real-time Kafka/FastAPI systems supporting 120K+ chargers at 99.99% event delivery. Addressed frequent schema drift by implementing SQLAlchemy/Flyway validation (60% reduction in drift issues) and deployed as Kubernetes microservices with GitHub Actions CI/CD; also has Airflow-based ingestion/crawling experience into Snowflake and stakeholder-facing delivery via a Fleetcharge PWA.”
Junior Full-Stack/AI Engineer specializing in web platforms and LLM applications
“Backend engineer from FoodSupply.ai who built and evolved a scalable restaurant/supplier product and order management platform using Node.js and REST APIs. Implemented a hybrid MySQL+MongoDB data architecture, optimized performance with Redis/Prisma, and led a phased migration with feature flags and a temporary sync layer to maintain data consistency. Strong focus on production security (OAuth2, RBAC, row-level security, AWS IAM) and reliability practices (testing with Pytest, Docker/AWS pipelines).”
Mid-level Software Engineer specializing in AI, full-stack systems, and FinTech
“Product-minded full-stack engineer with experience in fintech identity verification and industrial analytics, focused on turning repeated operational pain points into reusable platforms. Built real-time KYC/KYB dashboards, secure cross-platform web components, and a multi-tenant workflow engine that cut onboarding from 2 weeks to 1 day while materially improving conversion, reliability, and developer speed.”
Director-level Digital Marketing Manager specializing in SEO, Google Ads, and CRO
“Performance marketer with hands-on ownership of a $100K+/month Google Ads account, reporting up to 20x ROAS for a US-based Guardian Services client over a three-year engagement. Also shows broader growth expertise beyond paid media, including diagnosing technical SEO/site architecture issues at Admiral Casino, leading a programmer team, and expanding the site with 2,500 pages to restore traffic growth.”
Junior Backend/Infrastructure Engineer specializing in AWS distributed systems
“Backend engineer with 1.7 years of experience plus prior founding experience who has already owned production systems end-to-end in an early-stage environment. Most notably, they rebuilt a failing ingestion pipeline into a stable SQS/Fargate architecture that improved success from 40% to 100%, boosted throughput 10x, and cut processing time by ~75%, while also shipping an LLM-powered fashion search workflow using Vertex AI and Elasticsearch.”