Pre-screened and vetted.
Mid-level Full-Stack Software Engineer specializing in cloud microservices and AI search
“Robotics software engineer focused on backend/integration for indoor autonomous mobile robots, with hands-on ROS 2 experience integrating Nav2/AMCL/TF2 and LiDAR/camera pipelines. Emphasizes production readiness—robust failure recovery, QoS-tuned distributed communication, and strong observability (logging/health checks)—validated through Gazebo simulation, sensor-data replay debugging, and Docker-based CI/CD deployment.”
Junior Data Engineer specializing in data pipelines and streaming ingestion
“Backend/data platform engineer who owned a near-real-time patient feedback ingestion system, building a FastAPI + Kafka service with Snowflake/Airflow orchestration. Demonstrates strong production Kubernetes/GitOps practices on AWS EKS (Helm, Argo CD, Sealed Secrets) and solved real-time data integrity issues via idempotent processing with Redis.”
Mid-level Software Engineer specializing in full-stack cloud and agentic AI systems
“Backend engineer with hands-on ownership of production systems across maritime tracking, HR tech, and AI-powered document workflows. They combine strong operational instincts with measurable impact—cutting API latency from 10s to 3s, improving query performance by 60%, reducing deployment time by 50%, and driving 70% infrastructure cost savings with serverless design.”
Director-level AI Product Manager specializing in GenAI, LLMs, and SaaS platforms
“Technical Product/Program Manager with architect-level involvement who leads customer-facing product builds from sales discovery and Figma design through engineering estimation, schema decisions, and cloud deployment. Has shipped integrated ecommerce and auction products, including vehicle inventory workflows tied to Salesforce, Stripe, and QuickBooks, and has applied AI/ML to warehouse QA, defect detection, and pricing recommendations.”
Junior AI/ML Engineer specializing in LLM agents and RAG systems
“Built and deployed a production, multi-tenant modular agentic AI platform at Easybee AI, using LangChain/LangGraph with Redis-backed durable state to make agents reusable, traceable, and auditable. Emphasizes reliability via strict tool schemas, deterministic controllers, tenant-level policy enforcement, and regression testing derived from real production failures; also delivered AI automation for legal/finance workflows (attorney draw and expense automation) with explainable, deterministic payouts.”
Mid-Level Full-Stack Software Developer specializing in Java/Spring microservices and cloud
“Backend engineer who owned and shipped a campaign analytics API (FastAPI/Postgres/Redis/Celery) with ingestion from Instagram/YouTube, JWT auth, tests, and Docker deployment; improved performance from >1s to <150ms using precomputed aggregates and composite indexes. Experienced with Kubernetes GitOps using GitHub Actions + ArgoCD (zero-downtime rollouts, one-click rollbacks), Prometheus/Grafana observability, hybrid cloud-to-on-prem migrations, and real-time notification streaming via Redis Pub/Sub + WebSockets.”
Mid-level Software Engineer specializing in cloud and FinTech systems
“Backend/AI engineer who has built and operated production Node.js/Express services on AWS (Postgres/Redis) and has hands-on experience shipping an AI-powered support agent using RAG (Pinecone + LLM) with grounding checks and evaluation for hallucination rate. Demonstrates strong production reliability/performance debugging, including reducing peak latency from ~2s back to sub-300ms through query and caching optimizations, plus designing agent workflows with retries and human-in-the-loop escalation.”
Senior Engineering Manager specializing in AI platforms and cloud-native backend systems
“Player-coach engineering leader who stayed hands-on (coding/reviews) while leading delivery, including designing an event-driven AI workflow engine with explicit state modeling and robust retries. Built near real-time enterprise analytics for campaign measurement and drove reliability/process improvements (observability, incident runbooks, release management). Introduced lightweight CI/CD and automated testing to cut release time by ~40% while maintaining quality.”
Mid-level Full-Stack Java Developer specializing in cloud-native microservices and React
Mid-level Software Engineer specializing in cloud, DevOps, and distributed systems
Mid-level Data Scientist specializing in ML, data engineering, and real-time analytics
Senior DevSecOps/Cloud Engineer specializing in CI/CD and Infrastructure as Code
Mid-level MLOps/ML Engineer specializing in LLMs and financial risk modeling
Mid-Level Software Development Engineer specializing in backend microservices and cloud-native IoT
Mid-Level Full-Stack Software Engineer specializing in microservices and Generative AI
Mid-level Backend Software Engineer specializing in Java microservices and cloud platforms
Mid-level Software Engineer specializing in backend systems and FinTech microservices
Junior Full-Stack Software Engineer specializing in cloud-native microservices and data platforms
Mid-level Full-Stack Developer specializing in Java/Spring Boot, React/Angular, and cloud microservices
Senior Software Engineer specializing in AWS serverless, APIs, and data/ETL platforms
Mid-level Software Engineer specializing in distributed systems and cloud-native microservices
Executive Founder/CTO specializing in full-stack engineering and blockchain systems
Junior Full-Stack Software Engineer specializing in web, mobile, and cloud platforms