Pre-screened and vetted.
Mid-level Full-Stack Software Engineer specializing in cloud-native microservices
“DevOps engineer (State Farm) with hands-on ownership of Python backend services and data pipelines, deploying microservices and workers on Kubernetes using GitOps (Argo CD). Has led complex cloud-to-on-prem/hybrid migrations with staged cutovers and rollback planning, and built Kafka-based real-time streaming pipelines with schema governance, autoscaling, and strong observability.”
Intern Full-Stack/Cloud Engineer specializing in AWS, DevOps automation, and backend APIs
“Backend/cloud engineer with hands-on ownership of a climate data extraction pipeline (BeautifulSoup + Pandas ETL + CRON) that automated 50k+ monthly data points and removed ~20 hours/week of manual work. Also built a multi-AZ Kubernetes deployment for a Node.js system using Terraform and GitHub Actions (blue-green, rollbacks) and has Kafka/FastAPI experience from a healthcare plan management project.”
Intern Full-Stack Software Engineer specializing in web apps and AI integrations
“Computer science-oriented builder developing an iOS receipt-splitting app for real users (roommates), focusing on login security, receipt history storage, and future web access for broader usability. Demonstrates a practical, customer-facing mindset with structured integration/debugging practices (Dockerized environments, incremental testing, rollback strategy) and prior experience in communication-heavy retail/bakery roles.”
Mid-level Data Scientist & Product Ops/Analytics professional specializing in AI and KPI systems
“Cross-functional operator/chief-of-staff style leader who took a product from prototype to a live pilot in 3 months, spanning public-sector data normalization, an ML matching engine, a secure API, and KPI/investor demo instrumentation. Strong focus on executive alignment and productivity via Notion-based operating systems plus automated reporting (Python/Power BI), with experience supporting fundraising and go-to-market narratives.”
Senior Full-Stack Software Engineer specializing in cloud-native serverless systems
“Backend engineer who built a Node.js + SQL service integrating with the Google Ads API to periodically upload online and offline conversions via Azure Logic Apps, persisting upload records for ROI reporting. Implemented PII hashing, token validation, redundancy, and detailed failure/status logging for reliability and debuggability. Currently scoping an LLM/agent workflow (likely LangChain) to let marketing bulk-update e-commerce product data using SEO keywords without developer involvement.”
Mid-level Software Engineer specializing in Generative AI automation and secure platforms
“Backend/security-focused engineer from VeroTX who built an IdP service (Spring Boot + MongoDB on GCP) for an AI workflow platform and drove major latency improvements via caching and query/index optimization. Also shipped an AI loan-processing agent using LangChain/LangGraph, owning the document ingestion + vector database layer and designing a reliable multi-step workflow with retries, monitoring, and human-in-the-loop safeguards.”
Junior Software Engineer specializing in backend APIs and ML-driven systems
“Internship experience at Paycom owning an end-to-end personalized course recommendation feature for an LMS, spanning SQL-based data pipelines, ML integration, and FastAPI REST services for real-time recommendations. Focused on production tradeoffs (latency vs. accuracy), scaling/SQL optimization, and post-launch iteration driven by engagement metrics.”
Mid-Level Software Engineer specializing in full-stack, cloud, and data platforms
“Backend/full-stack engineer who has owned production TypeScript systems in both fintech-style transaction/rewards flows and HIPAA-regulated healthcare platforms. Deep focus on correctness and reliability (idempotency, retries/DLQs, reconciliation, observability) plus strong infra automation (Docker/Terraform/CI-CD) and measurable performance wins (40% query improvement, 90% test coverage).”
“Game design capstone project owner who built and tuned a full steal/sell/upgrade progression economy for a house-robbery game, including item weight/value balancing, upgrade pacing, and difficulty gates (police/NPC detection). Iterated via playtests and basic telemetry signals (purchase rates, item selection) and implemented a code-driven item attribute system to speed tuning, while also negotiating scope tradeoffs with the team around adding minigames.”
Mid-level Software Engineer specializing in AI RAG systems and full-stack cloud applications
“AI/LLM engineer who shipped a production RAG-based knowledge assistant at SparkPlug serving 10,000+ daily users, streaming GPT-4 answers with inline citations over WebSockets. Demonstrated measurable impact (support resolution time cut 18→12 minutes; retrieval precision +~20%) and strong production rigor across ingestion, monitoring/alerting, evaluation, and messy ERP-style data integration with validation, RBAC, and idempotent operations.”
Executive CIO and Enterprise Architect specializing in cloud, security, and IT governance
“Fractional CIO/founder-type operator at AHDX Inc, a hybrid-cloud/primary storage solutions startup with a compliance focus targeting healthcare; MVP has completed beta and the company has seed funding while pursuing additional investment. Has supported multiple startups (OmniHR, Combat Connect, 3BX) and cites tangible results tied to DoD/security, Medicare/Medicaid, and Air Force LMS contracts, positioning them as a hands-on "fixer" for early-stage technical strategy and architecture.”
Mid-Level Software Engineer specializing in cloud-native microservices
“Built and shipped both a solo real-time multiplayer Spades game (TypeScript monorepo with shared client/server engine) and a production internal LLM-powered document Q&A tool for a SaaS company. Demonstrates strong RAG pipeline design (Pinecone + embeddings + reranking), rigorous eval/regression practices, and pragmatic data ingestion/observability work across Confluence, Notion, and messy PDFs/OCR—backed by clear metric improvements (P@1 61%→78%, escalations 40%→22%).”
Mid-level Applied ML Engineer specializing in LLM evaluation and multimodal agent systems
“Full-stack engineer working at the intersection of product and infrastructure, building developer-facing interfaces for AI voice agents in XR/immersive environments plus telemetry-heavy analytics dashboards. Experienced in Postgres telemetry data modeling and performance tuning, and in designing durable multi-step LLM pipelines with idempotency, retries, and strong observability; has operated in fast-moving startup-like teams (Biocom, HandshakeAI).”
Mid-level Full-Stack/MES Software Engineer specializing in manufacturing systems
“Software engineer with hands-on experience delivering production-floor applications in manufacturing environments: built a PDA-friendly web app integrated with Oracle PL/SQL and deployed it on-site in a live warehouse, then iterated via tight feedback loops. Also rebuilt a broken assembly QR label printing workflow as a WPF Windows desktop tool and rolled it out across factory processes with operator training; additionally built a TypeScript/Node/Express/MongoDB app deployed on AWS (EC2/S3).”
Mid-level Machine Learning Engineer specializing in computer vision and reinforcement learning
“Early-stage engineer with hands-on embedded prototyping experience (Arduino/Raspberry Pi) who helped build an award-winning smart glasses project enabling phone notifications via Bluetooth. Strong computer vision performance optimization background, including accelerating 120 FPS inference by moving from TensorFlow to PyTorch and deploying through ONNX + TensorRT quantization, plus Docker-based GPU deployment and CI/ML practices.”
Entry-Level Software Engineer specializing in full-stack and machine learning
“Robotics software builder who delivered an end-to-end gesture-controlled drone system using an ESP32+IMU stream and real-time ML inference mapped to Tello SDK commands. Drove reliability improvements by instrumenting the pipeline with timestamps/logging and matching training vs runtime preprocessing, reaching ~94% gesture classification accuracy; experienced with Docker/Compose for reproducible multi-service deployments.”
Mid-Level Full-Stack Engineer specializing in AWS serverless and React/Node.js
“Backend engineer who built and evolved a serverless AWS platform for large-scale live screening events with real-time chat/feedback and streaming (API Gateway/Lambda/DynamoDB/WebSockets/IVS, IaC via Pulumi). Led production refactors and phased migrations using feature flags and dual-write strategies, and has hands-on experience implementing JWT auth, RBAC, and database-enforced row-level security for multi-tenant systems.”
Intern Software & AI Engineer specializing in distributed systems and LLM applications
“Stony Brook Fall 2024 capstone contributor who built a ROS2-based warehouse mobile robot prototype, owning perception and SLAM integration end-to-end. Strong in real-time robotics optimization on Jetson Orin (TensorRT/CUDA, ROS2 tracing/Nsight) and in distributed ROS2 communications (DDS discovery/QoS, MAVLink-to-ROS2 bridging), with a full simulation/testing/deployment toolchain (Gazebo, CI tests, Docker/K3s).”
Entry-Level Full-Stack Software Engineer specializing in serverless AWS and AI applications
“Built and deployed serverless AWS applications (Lambda/S3/RDS Proxy) including a NASA L’Space React + Python data analysis tool, focusing on performance for large datasets. Demonstrates strong cloud troubleshooting across compute and networking (CloudWatch-driven diagnosis, EC2 scaling, security group fixes) and a user-driven iteration loop that improved product usability with dynamic filtering and interactive UI.”
Senior Full-Stack Software Engineer specializing in scalable web apps, cloud, and blockchain/AI
“Full-stack engineer with strong production ownership across React/TypeScript, Node.js, and AWS (EC2/ECS/RDS/CloudWatch), including CI/CD, observability, and incident response. Delivered a secure RBAC workflow module end-to-end and achieved measurable gains (~30–40% latency reduction, ~50% error reduction) that lowered infra/ops costs. Comfortable in high-ambiguity startup environments—shipped a payment module within 2 days of joining with no documentation.”
Mid-level Full-Stack AI Engineer specializing in healthcare and enterprise SaaS
“Full-stack product engineer who has built AI-assisted CRM and agent workflows in Project SARA and operational systems like payroll for a staffing platform. Stands out for combining React/TypeScript, Django/Postgres, real-time systems, and LLM orchestration with strong product instincts—delivering measurable gains in response time, conversion, and engineering leverage.”
Mid-level AI/Data Engineer specializing in agentic AI and data platforms
“AI/LLM engineer who built a production resume-parsing and candidate-matching platform at Quadrant Technologies, combining agentic LangChain workflows, VLM-based document template extraction (~85% accuracy), and a hybrid RAG backend for resume-to-JD search. Notably integrated automated LLM evals and metric-based CI/CD quality gates to catch silent prompt/model regressions, and led a 3-person team across frontend/backend/testing.”
Mid-level Software Engineer specializing in AI, backend systems, and cloud platforms
“Full-stack engineer who helped build and launch an internal genAI platform called GAIL, supporting multiple LLMs, confidential document upload for RAG pipelines, and collaborative chat. Worked across FastAPI, React/TypeScript, AWS/DynamoDB, and Azure, with notable ownership of backend RAG logic, MCP integration architecture, and frontend fixes that improved chat usability.”
Mid-level Full-Stack Engineer specializing in modern web applications
“Built and launched a production AI chat assistant inside a data processing platform, focused on helping users understand large table outputs and job results faster. Brings strong end-to-end product engineering across React/TypeScript frontend, backend APIs, and LLM integration, with a clear emphasis on reliability, safe behavior, and iterative quality improvements after launch.”