Pre-screened and vetted.
“Backend engineer focused on real-time, event-driven systems (Java microservices) handling high-frequency data with low-latency and reliability requirements. Strong in Kafka-based asynchronous architectures, Redis caching, JVM/query tuning, and scalable deployments on Docker/Kubernetes with Jenkins CI/CD; no direct ROS/robotics experience but has closely related distributed communication patterns.”
Senior Site Reliability Engineer specializing in cloud observability and incident response
“Backend engineer experienced in evolving high-scale legacy on-prem systems into cloud-native, event-driven microservices on AWS/Kubernetes (noted peak traffic ~1.5M QPS). Strong focus on reliability engineering and operational excellence—SLO-driven observability, GitOps/canary rollouts, chaos testing, and preventing cascading failures (e.g., retry-storm mitigation).”
Junior Software Engineer specializing in cloud administration and Python/ML
“Backend/data engineer with hands-on production experience across Azure and AWS: built FastAPI + PostgreSQL services with Azure AD OAuth2/JWT auth and strong reliability patterns (timeouts, retries, correlation IDs). Delivered AWS Lambda/ECS solutions with Terraform/CI-CD and cost controls (SQS buffering, reserved concurrency), and built/operated AWS Glue ETL pipelines into Redshift while modernizing legacy SAS reporting into Python microservices with parity testing.”
Director-level Unity/XR Developer specializing in VR/AR and mixed reality applications
“Freelance Unity/XR developer with multiple Meta Quest projects (including non-game XR apps) and a 1st-place win at Meta’s Sense AI hackathon in Barcelona for an AI camera-access VR assistant for vehicle repairs. Built a VR Spanish-learning experience solo and has hands-on experience optimizing VR performance (culling, view restriction) and integrating voice recognition for language interactions.”
“Frontend product builder who has shipped and maintained a two-mobile-app ecosystem (user + employee) backed by Node.js, emphasizing separation of concerns, shared libraries for reuse, and TypeScript type safety. Re-architected a Sunmor Research codebase using MVC, improving readability and collaboration and taking the product from unusable to working, with a strong regression-testing mindset and customer-feedback-driven iteration.”
Senior/Lead Unity Developer specializing in mobile games, AR, and multiplayer integrations
“Unity gameplay engineer with AAA experience who built a highly configurable weather/day-night system (clouds/rain/sun-moon/stars) that influenced core gameplay decisions (vehicles, time-of-day, farming/animal needs). Also has hands-on multiplayer experience with Photon Fusion (including client-backend communication and physics sync troubleshooting) and has set up CI/CD and build pipelines.”
Junior Data Engineer specializing in LLM agents and RAG pipelines
“Built and deployed “ApartmentFinder AI,” a multi-agent system using Google ADK, Gemini, and Google Maps MCP to automate apartment shortlisting and commute-time analysis, cutting a 45–70 minute user workflow down to ~30 seconds. Also has strong delivery/process chops from serving as an SDLC Release Coordinator, managing 52+ releases and reducing SDLC issues by 84%.”
Mid-level Software & ML Engineer specializing in agentic LLM systems and ML infrastructure
“Built and deployed an LLM-to-SQL automation system in a closed/internal environment, using a retriever–reranker–validator architecture on Kubernetes with strong security controls (semantic + rule-based validation and RBAC), achieving 99% uptime and cutting manual query time ~40%. Also worked on genomic sequence classification and semantic search workflows, orchestrating data prep with Airflow, tracking/deploying with MLflow, and optimizing distributed multi-GPU training on a university Kubernetes cluster.”
Mid-level Data Scientist specializing in NLP, recommender systems, and ML deployment
“At Provenbase, built and shipped a production LLM-powered semantic search and candidate matching platform (RAG with GPT-4/Gemini, multi-agent orchestration, Elasticsearch vector search) to scale sourcing across 10M+ candidate records and 1000+ data sources. Drove sub-second performance, cut LLM spend 30% with routing/caching, and improved recruiting outcomes (+45% sourcing accuracy; +38% visibility of underrepresented talent) through bias-aware ranking and tight collaboration with recruiting stakeholders.”
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.”
Mid-level Site Reliability Engineer specializing in cloud infrastructure and Kubernetes
“Backend/infra-focused engineer who owned production systems for distributed ML experimentation (hyperparameter tuning across a cluster with GPU scaling, custom scheduling, and checkpoint-based fault tolerance). Also built and operated a low-latency log validation service using queued async workflows with idempotency, retries/backoff, and strong observability, plus experience building resilient Selenium-based browser automations for complex multi-step web flows.”
Senior Engineering Manager specializing in distributed systems and Kubernetes
“India-based engineering leader/player-coach managing ~20 people and three products, while still shipping hands-on in Python/Golang across 8–10 microservices deployed on GCP (Kubernetes) and AWS (ECS). Has led end-to-end delivery (design through QA) and owned production reliability improvements (including building a Slack alerting bot). Strong domain exposure in utilities (MDM/meter readings, billing/rate calculations) and financial integrations (GL code tagging), plus side projects in Golang around LLM API cost-optimization.”
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.”
Mid-level Software Engineer specializing in real-time IoT and event-driven platforms
“Founding engineer at a startup building LLM/agentic workflows for public-safety customers, with hands-on experience delivering a hybrid on-prem + secure cloud solution to meet strict compliance needs. Implemented OpenTelemetry observability for multimodal agentic systems behind closed networks and used the resulting traces to optimize prompting/token usage for customer-specific security integrations. Regularly runs technical workshops and supports pre/post-sales by translating integration feedback into product roadmap decisions.”
Mid-level AI Engineer & Researcher specializing in healthcare AI and multimodal LLM systems
“Backend/ML engineer focused on clinical AI transparency who built ShifaMind, an explainability-enforced clinical ML system using UMLS/MIMIC-IV/PubMed data with RAG, GraphSAGE, and cross-attention. Demonstrated strong production engineering via FastAPI API design and safe migrations (feature flags/shadow inference), plus HIPAA-aligned auth/RLS patterns; also delivered a real-time comet detection system reaching 97.7% accuracy.”
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.”
Junior Machine Learning Engineer specializing in LLM fine-tuning and semantic retrieval
“Backend engineer with legal-tech and AI workflow experience: built JurisAI, an end-to-end legal research system using OCR + embeddings + Pinecone vector search to deliver citation-grounded LLM answers with safe failure modes (~90% recall@K). Also led a GW Law metadata migration into Caspio with batch validation and parallel rollout, and has strong FastAPI/GCP production reliability and observability practices.”
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.”
Mid-level Backend Engineer specializing in distributed systems and industrial IoT
“Backend/Python engineer focused on real-time sensor/IoT analytics: built dashboards and a high-throughput ingestion pipeline (MQTT -> Python worker -> TimescaleDB) with buffering, batch inserts, and validation. Strong Kubernetes + GitOps practitioner (Dockerized microservices, HPA, probes, ArgoCD) who has handled production incidents like CrashLoopBackOff under peak load and supported an on-prem analytics migration to AWS using shadow traffic and rollback plans.”
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.”
Mid-level Software/Data Engineer specializing in cloud ETL pipelines and data infrastructure
“Backend/data engineer who built a production analytics data service (Python/FastAPI on AWS/Postgres with PySpark ETL) handling millions of records per day and drove major latency improvements (10–15s to <2s) via indexing, Redis caching, and shifting aggregations into ETL. Also shipped an LLM-based natural-language-to-SQL assistant end-to-end with strong guardrails (schema restrictions, read-only validation, RBAC, masking) and designed a multi-step agent workflow with verification and fallback logic.”
Director-level Software Development Leader specializing in FinTech, Blockchain, and AI
“Bootstrapped founder with a technical background who has already built an MVP SaaS loyalty and referral platform plus a tablet/mobile POS companion product, leveraging Azure and Google Cloud support rather than outside capital. Focused on learning-by-building, resource-efficient execution, and forming highly motivated, equity-aligned teams.”
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.”