Pre-screened and vetted.
Senior Full-Stack Engineer specializing in .NET, Angular, Azure, and AI automation
Intern Backend Software Engineer specializing in AI and distributed systems
“Built and owned an enterprise AI document-processing deployment at an automotive tech startup, taking it from discovery to stabilization. Strong in production LLM/RAG systems and backend reliability, with measurable impact including 8,000+ documents processed monthly and turnaround time reduced from nearly 24 hours to about 3 hours.”
Mid-level Data Scientist specializing in ML, LLMs, and Azure MLOps
“Cloud/ML engineer with production deployment experience on Azure (Dockerized models, managed APIs, data pipelines) who has repeatedly stabilized unreliable systems—e.g., taking an API-driven analytics pipeline from ~60% to 98% reliability and an Azure ML service from ~80% to 97% by addressing rate limits, container memory, and gateway timeouts. Also built an explainable contract-risk model for entertainment bookings (Transformers + SHAP) and integrated it into a legacy booking system via a Flask REST API, plus prior IoT work at Nissan processing CAN bus sensor streams for diagnostics/anomaly insights.”
Senior QA Engineer specializing in test automation and API/E2E testing
“QA automation engineer with 7+ years across finance/healthcare/utility/services, specializing in Selenium + Cucumber and building automation frameworks. Has tested machine-learning-powered claims prediction features and uncovered complex timing/concurrency failures in subscription payments by simulating delayed webhooks and parallel execution, then driving production fixes end-to-end using disciplined Jira workflows.”
Director of Engineering specializing in AI-enabled SaaS and mobile platforms
“AI startup co-founder and CTO who helped raise $2.6M in seed funding at RedRex and drove product strategy from ideation through execution. Experienced with rapid experimentation and AI-driven prototyping to validate ideas quickly, and has direct exposure to the VC/accelerator ecosystem (Gener8tor) with a market-first approach to building and pitching startups.”
Junior Full-Stack Engineer specializing in AI and distributed systems
“Built and owned a hackathon project (Gritto) with a Python/FastAPI backend that routes user text through a sequence of Gemini agents to produce structured JSON outputs. Has hands-on production deployment experience using Docker/Docker Compose, GitHub Actions CI/CD, AWS App Runner, MongoDB, and secrets management (Doppler + migration to AWS Secrets Manager), plus implemented a chat-like experience via multiple HTTP requests when SSE wasn’t viable.”
Junior Embedded Systems Engineer specializing in IoT and automotive firmware
“Customer-facing embedded/IoT engineer with experience taking lab prototypes into production, including an IoT medical facility integration where they re-architected firmware with RTOS scheduling, added health monitoring/fault recovery, and implemented secure OTA updates. Strong at real-time diagnosis using end-to-end observability and at tailoring technical demos for both embedded and cloud developer audiences (MQTT/device shadows), helping drive customer confidence and broader deployments.”
Entry-Level Software Engineer specializing in distributed systems and backend infrastructure
“Built and operated an end-to-end customer-facing "Record Platform" web product as both engineer and primary user, focusing on reliability and correctness in core flows like search and checkout. Implemented a TypeScript/React frontend with a multi-service backend and Kafka-based event-driven architecture, and created internal tooling to automate risky ops like Kubernetes TLS certificate rotation with k6 load/chaos testing (including HTTP/2 and HTTP/3 validation).”
Junior Full-Stack Software Engineer specializing in Node.js microservices and React
“Backend engineer who has shipped both high-throughput real-time systems and production LLM/RAG features. Built a database-free, local-first messaging service (Node/Express/Socket.IO) achieving ~1,500 msgs/sec at <25ms p95, and implemented a Go-based RAG recommendation pipeline with strict JSON/schema validation, catalog grounding, fallbacks, and eval loops that cut hallucinations to ~1–2% while reducing LLM costs ~60%.”
Senior Full-Stack Software Engineer specializing in IIoT, Edge AI, and real-time analytics
“Full-stack engineer who built an end-to-end low-code/no-code IDE for creating AI/ML workflows for industrial IoT sensors using Next.js/TypeScript and NestJS microservices. Focused on scaling high-volume sensor dashboards—improved UX and performance via WebSockets, debouncing, pagination, and API payload reduction—validated with profiling tools and user feedback in a startup environment.”
Senior Data Scientist/Software Engineer specializing in ML systems and cloud DevOps
“AI software engineer with experience spanning LLM/RAG production systems and regulated fintech infrastructure. Built an end-to-end natural-language-to-SQL analytics assistant (Weaviate + GPT-4 + Supabase) shipped as an API with 92% accuracy and major time savings for non-technical users, and also owned demand-forecasting and CI/CD/containerization improvements for a Bank of America core banking deployment at Infosys.”
Mid-level QA Engineer specializing in Agile test planning and automation
“QA tester with hands-on API and web testing experience (functional, E2E, regression, sanity, performance) looking to transition into console game testing. Understands the need for platform-specific validation across console models/firmware and is aware of Sony TRC, Microsoft XR, and Nintendo LOT certification requirements, with a structured, risk-based approach to prioritization and release support.”
Senior Mobile Software Engineer specializing in secure React Native and Bitcoin wallets
“Built and evolved the backend-adjacent platform for a self-custody Bitcoin wallet used by 2000+ users, emphasizing security-first architecture that avoids custodial risk by keeping private key operations client-side. Demonstrates strong API reliability and security depth (FastAPI contract-first design, idempotency, state-machine modeling, JWT/device-aware auth) and has reduced production failures by hardening signing flows against poor connectivity.”
Mid-level Full-Stack Developer specializing in Java, Spring Boot, and cloud-native web apps
“Full-stack engineer with strong React/TypeScript and Java Spring Boot microservices experience who has built end-to-end task management and real-time, data-intensive dashboards. Demonstrates practical depth in security (JWT, RBAC, token refresh), performance optimization (indexing/aggregations, virtualization, caching), and cloud deployment (AWS, Docker, Jenkins, Kubernetes).”
Mid-Level Full-Stack Software Engineer specializing in cloud-native microservices
“Backend engineer with cloud-native Python/Flask experience building high-throughput financial platforms (loan origination intelligent document processing and real-time fraud detection). Has scaled microservices on AKS with event-driven Azure messaging, delivered measurable performance gains (e.g., 700ms→180ms query latency; ~40% API improvements), and implemented strong security controls (OAuth2/JWT, Azure AD RBAC, audit logging, AES-256/TLS) for sensitive regulated data.”
Senior QA Automation Engineer specializing in test automation and CI/CD quality gates
“QA automation engineer focused on end-to-end quality for a CMS lien registration workflow, owning a Playwright-based regression suite covering high-risk paths (creation, amendments, cancellation, batch file validation). Demonstrated impact by catching a UI change that bypassed required-field validation pre-release, stabilizing flaky CI tests using network-response signals, and driving clearer acceptance criteria and observability improvements (request IDs in logs) through cross-functional collaboration.”
Senior Full-Stack Developer specializing in cloud-native FinTech and AI platforms
“Full-stack engineer with strong production ownership: built and operated a real-time transaction monitoring/fraud-alerting system using Java Spring Boot, Kafka, Docker, and AWS with CI/CD. Demonstrates metrics-driven operations (latency, stability, consumer lag, true/false positives) and reliability patterns for integrations (idempotency, retries/backoff, DLQs, reconciliation/backfills), plus modern React/TypeScript + Node/Postgres architecture experience.”
Mid-level Full-Stack Developer specializing in cloud-native APIs and data workflows
“Built and owned end-to-end ordering and inventory/order management systems for a wholesale distributor, delivering an MVP quickly and iterating based on direct observation of daily users. Experienced with TypeScript/React + Node.js layered architectures and microservices using RabbitMQ, including real-world scaling issues (duplicates, backpressure) and observability practices (correlation IDs, structured logging).”
Mid-level AI Engineer specializing in multi-agent systems and RAG
“Built and shipped a production LangGraph-based multi-agent LLM analytics/decision copilot that answers questions across SQL/BI systems and unstructured docs, emphasizing grounded, tool-verified outputs with citations and confidence gating. Deep hands-on experience with orchestration (LangGraph, CrewAI, OpenAI Assistants, MCP) plus real-world latency/cost optimization (vLLM batching/KV caching, speculative decoding, quantization) and rigorous eval/observability. Partnered closely with business/ops stakeholders to deliver explainable reporting automation, cutting manual reporting time by 50%+.”
Mid-level Full-Stack & Integration Engineer specializing in Insurance APIs
“Hands-on engineer focused on taking complex/LLM-style workflows from prototype to production, emphasizing robust error handling, CI/CD + Docker deployment, and deep observability (Kibana/Rancher/Grafana). Experienced customizing client integrations and data transformations (XML/JSON/PDF to SFTP) and debugging agent workflows with traces, prompt verification, and human-in-the-loop safety controls. Partnered with product/ops to drive adoption, including a MuleSoft migration that improved partner onboarding speed by ~50%.”
Mid-Level Software Engineer specializing in cloud-native microservices on AWS and Kubernetes
“Backend engineer who built a stateless Python/Flask service supporting a healthcare-document ETL pipeline, offloading heavy processing to Celery workers and adding strong observability (metrics, structured logs, audits). Demonstrates practical performance/reliability work: batch chunking, priority queues, autoscaling by queue depth/CPU, DLQ routing, and PostgreSQL tuning (indexes, pagination) to cut slow API responses. Also has experience deploying real-time ML classification via TensorFlow Serving behind a FastAPI wrapper and integrating models via REST/gRPC.”
Junior Embedded Software Engineer specializing in IoT and microcontrollers
“Embedded/software engineer with hands-on Raspberry Pi work building a WhatsApp-controlled camera/servo system using TCP/IP plus Selenium automation of WhatsApp Web. Brings production DevOps experience from Infosys (Docker/Kubernetes, CI/CD, microservices, Kafka) and a methodical hardware/software debugging workflow using lab tools like oscilloscopes and multimeters.”
Mid-level Backend Engineer specializing in APIs, microservices, and data platforms
“Software engineer who built JobIntel, an end-to-end Python ETL pipeline integrating ATS data from platforms like Greenhouse using Scrapy and FastAPI. Stands out for production reliability work: designing async fault-tolerant architecture, optimizing PostgreSQL write-heavy upserts, and building a Prometheus/Splunk observability stack that cut debugging from hours to minutes.”
Mid-level Software Engineer specializing in full-stack and cloud-native backend systems
“Full-stack/backend-leaning engineer with hands-on experience building transaction-processing systems using React, TypeScript, Node.js, MySQL, and Spring Boot microservices. They have owned services in production on AWS EKS, diagnosed peak-traffic failures via CloudWatch, and driven architectural modernization to Kafka-based microservices that improved scalability, deployment speed, and reliability.”