Pre-screened and vetted.
Mid-level Software Engineer specializing in cloud and full-stack web development
Mid-level QA Engineer and Full-Stack Developer specializing in Apple platforms and ML
Junior Software Engineer specializing in AI/ML and FinTech full-stack development
Intern Software Engineer specializing in full-stack and cloud development
Junior Software Engineer specializing in cloud infrastructure and full-stack development
Mid-level Software Development Engineer specializing in AWS cloud services and distributed systems
Software Engineer specializing in distributed systems, cloud cost analytics, and AI/ML platforms
Junior Software Developer specializing in C++ systems and performance engineering
Software Engineer specializing in distributed systems, cloud cost optimization, and AI/ML
Junior Software Engineer specializing in cloud infrastructure and database tooling
Mid-level Software Engineer specializing in cloud-native platforms and healthcare systems
“Backend engineer with healthcare-domain experience building a security-critical RBAC identity/authentication/authorization microservice suite used across hospital imaging platforms (X-Ray, Ultrasound, etc.). Demonstrates strong security mindset (mTLS, cert hygiene, JWT, pen-testing collaboration) and pragmatic scaling/reliability practices (Nginx load balancing, Redis caching, automated tests, canary rollouts).”
Executive HR Tech & Salesforce Architect specializing in AI-driven recruiting automation
“Co-founder of an HR tech startup who took an LLM-centered skill intelligence engine from prototype to production to deliver explainable, skill-based resume insights as an alternative to black-box ATS screening. Previously worked in consulting (Deloitte, Stand Up, Brilio), with experience in technical demos/workshops, pre-sales scoping, and supporting large deal cycles (including a ~$1M UK automotive client).”
Mid-Level Backend/Cloud Engineer specializing in AWS/Azure microservices
“Full-stack engineer who built a smart loan approval workflow for a Goldman Sachs hackathon (React/Node/Express/Postgres) including KYC handling, reviewer queues, and an ML-based pre-scoring/auto-reject step. Also has Amazon internship experience driving a customer-facing long-polling change that reduced empty requests by 84%, and demonstrates strong system design depth in real-time voice + LLM streaming architectures.”
Mid-Level Full-Stack Software Engineer specializing in event-driven data platforms
“Backend engineer with SAP experience modernizing a legacy Flask/PostgreSQL product master data platform into a modular, stateless, containerized service with Kafka-based background processing and improved observability. Also has hands-on academic/side-project experience operationalizing ML (NLP retrieval with TF-IDF/BERT via FastAPI and CV lane-edge detection inference APIs using PyTorch).”
Mid-level Software Engineer specializing in ML platforms and cloud-native backend systems
“Software engineer with experience at Google and the City and County of San Francisco building production AI systems, including a RAG-based internal support chatbot and ML-driven ticket priority tagging. Has scaled data/ML platforms with Airflow on GCP (1M+ records/day, 99.9% SLA) and deployed multi-component systems with Docker and Kubernetes (GKE), using modern LLM tooling (LangChain/CrewAI, Claude/OpenAI, Pinecone/ChromaDB, Bedrock/Ollama).”
Junior Embedded Systems & Wireless Software Engineer specializing in BLE/Wi-Fi performance
“Master’s capstone contributor on an autonomous rover navigation project, serving as an embedded/robotics software designer. Built low-level wheel control and odometry from encoders, integrated RealSense and RPLidar via ROS, and solved sensor-fusion/coordinate-frame issues by creating custom TF transforms. Used Gazebo to debug sim-to-real behavior and improved reliability on rough terrain by moving to dual-channel encoders when IMU data proved unreliable.”
Mid-level Full-Stack Software Engineer specializing in cloud, microservices, and React/Java
“Software engineer with experience at PayPal and JPMC building large-scale onboarding/account setup systems using React/TypeScript with Spring Boot/Node microservices and Kafka. Also built an Ignition-based SCADA monitoring tool at Mainspring Energy that became the default for manufacturing/test engineers by aggregating real-time telemetry and historical test data.”
Intern AI/ML Engineer specializing in Generative AI and applied machine learning
“New graduate with hands-on LLM work building a RAG pipeline (HNSW, lexical reranking/boosting, ReAct) and optimizing it through ablation to dramatically reduce latency. Also building a modular personal assistant with a custom wake word model, router-driven agent selection, and integrations like Spotify with secrets managed via .env.”
Junior Software Engineer specializing in distributed systems and backend microservices
“Distributed systems engineer (ex-Nykaa, Licious) who built a PBFT-based Byzantine fault-tolerant consensus system in Go for a multi-node banking-style application, including checkpointing and automated failover/leader election. Strong production reliability background with Docker, Jenkins CI/CD, and monitoring/on-call troubleshooting using Grafana and New Relic; no direct ROS/robotics hardware experience yet but has highly transferable multi-node coordination expertise.”
Junior AI Engineer specializing in LLM pipelines, RAG, and computer vision
“Built and deployed an on-prem, HIPAA-compliant LLM pipeline for oncology-focused clinical note generation and decision support, emphasizing grounded differential diagnosis and explainable reasoning via RAG to reduce hallucinations. Also created a LangGraph-based multi-agent academic paper search system integrating Tavily, arXiv, and Semantic Scholar with an orchestrator that routes tasks to specialized sub-agents.”
Intern Software Engineer specializing in data pipelines and full-stack web development
“Internship at Radar (geolocation infrastructure) where they owned automation of multiple geospatial data ingestion pipelines (including US/Canadian address ingestion), orchestrating Spark (Scala) jobs via Python-based Airflow and using GitOps-style CI/CD workflows.”