Pre-screened and vetted.
Senior Technical Support Engineer specializing in cloud and distributed systems
Mid-Level Full-Stack Software Engineer specializing in Cloud, Microservices & Distributed Systems
Mid-level AI/ML Engineer specializing in cloud MLOps and scalable model deployment
Senior Software Engineer specializing in backend systems, AWS cloud services, and data pipelines
Senior Backend Software Engineer specializing in automation microservices
“Backend Python engineer who built core services for a telecom automation engine monitoring thousands of routers in real time and auto-generating support tickets. As the sole Intelygenz engineer on the project, they diagnosed a costly Terraform/GitLab CI/CD resource-leak issue in AWS and implemented a cleanup redesign that eliminated orphaned resources and reduced client cloud spend. Also shipped applied-AI ticket triage suggestions via API integration and built an end-to-end Gmail-to-ticket ingestion workflow.”
Mid-Level Software Engineer specializing in backend, cloud, and event-driven systems
“Robotics software engineer focused on backend and distributed systems for real-time robot operations, including sensor ingestion, robot state management, and robot-to-cloud communication. Hands-on with ROS/ROS2 integration and real-time navigation debugging, plus production-grade monitoring, CI/CD, and containerized deployments (Docker/Kubernetes) to improve stability and performance.”
Senior Software Engineer specializing in backend, DevOps, and LLM-powered systems
“Backend-focused Python engineer who has owned production FastAPI services deployed on Kubernetes, including CI/CD (GitLab CI to ECR) and GitOps delivery via ArgoCD/Helm. Has hands-on experience with complex reliability and infrastructure work—solving data inconsistency with validation/partial-data paths, fixing K8s liveness issues via lazy loading, and supporting a phased cloud-to-on-prem migration with dual-writes and monitoring. Also built Kafka-based real-time ingestion consumers handling bursty, high-throughput traffic with async processing and topic/retention tuning.”
Mid-Level Full-Stack Software Engineer specializing in cloud-native microservices
“Backend engineer with experience in both healthcare (Siemens) and payments (Bitwise), focused on scaling Python APIs and modernizing architectures. Has led monolith-to-microservices migrations and introduced Kafka async processing, Redis caching, and ELK observability, citing ~40% faster issue resolution and improved reliability via idempotency and strong security controls (OAuth2/JWT, RBAC, RLS).”
Mid-Level Software Engineer specializing in full-stack and backend systems
“Full-stack JavaScript developer in small-company environments building PCB manufacturing web tooling. Owned and delivered blob-storage upload/download infrastructure (including an internal developer library) and a training/compliance tracking tool. Implemented secure, broadly compatible SSO for a customer portal under a <1 month deadline tied to an 8-figure customer deal, despite having no prior authentication experience.”
Mid-level Full-Stack Developer specializing in healthcare cloud applications
“Master’s-program backend engineer with strong Java/Spring Boot industry experience who also owned a Python analytics service (Flask/Postgres, JWT, Celery/Redis) and optimized large-dataset performance via SQL/batching. Has hands-on Kubernetes microservices deployment and GitLab+Terraform CI/CD/GitOps workflows, plus experience supporting phased on-prem to AWS migrations and building Kafka-based real-time streaming pipelines.”
Mid-level Java Full-Stack Developer specializing in microservices and AWS
“Full-stack engineer (HCL Tech) with 4 years building enterprise, high-throughput microservices on AWS/Azure using Java/Spring Boot and React. Demonstrated measurable performance gains (40% throughput) through Redis caching, deep SQL/query tuning, and Kafka-based async refactors, plus strong DevOps/observability practices with Jenkins/CloudFormation and Datadog/Splunk.”
“ML/LLM engineer with production experience building a RAG-based LLM support assistant (FastAPI, Redis, Kafka) with multi-layer validation and human-in-the-loop feedback loops to improve accuracy over time. Has orchestration and MLOps depth using Airflow and Kubeflow on Kubernetes (autoscaling, alerting, monitoring) and delivered measurable ops impact (40% ticket efficiency improvement) by partnering closely with customer support teams.”
Mid-level Software Engineer specializing in Java microservices and ML model integration
“Backend/ML platform engineer who owns end-to-end delivery of ML-serving APIs (FastAPI + TensorFlow) and runs them reliably on Kubernetes using ArgoCD GitOps. Has hands-on experience solving production-only issues (probe tuning for model warm-up, resource profiling) and building scalable Kafka streaming pipelines, plus supporting phased on-prem to AWS migrations with dependency discovery and recreation of hidden jobs/workflows.”
Mid-level Full-Stack Java Developer specializing in cloud-native microservices
“Software engineer with experience at Synchrony and HCL delivering end-to-end production systems: a secure, Kafka-driven transaction processing microservice with React real-time status tracking, containerized and deployed on AWS Kubernetes via Jenkins with ELK/CloudWatch monitoring. Has hands-on incident ownership and performance tuning (DB/query/index/pooling) driving ~20–30% latency improvements, plus built internal Python monitoring APIs with strong reliability and observability.”
Mid-level Full-Stack Software Developer specializing in cloud-native microservices
“Built a real-time telemedicine clinician dashboard and iterated post-launch by diagnosing lag via logs/metrics and optimizing DB queries/sync logic. Also shipped a production internal RAG knowledge assistant for support teams, including embeddings/vector DB, citation-only answers with abstention thresholds, and an eval loop driven by real ticket data that improved accuracy through chunking/overlap and batching optimizations.”
Senior Linux Systems Engineer specializing in hybrid cloud and DevOps automation
“Cloud/infrastructure engineer from ASM Research supporting federal healthcare systems, operating multi-cloud (AWS/Azure/GCP) environments at ~2000-server scale. Deep hands-on experience with Terraform/Ansible IaC, PR-based governance (Atlantis), and secure CI/CD (OIDC/least privilege), with concrete incident response wins and HA/failover testing improvements. Not an IBM Power/AIX specialist but comfortable translating virtualization/partitioning and ops practices to new platforms.”
Mid-level Full-Stack & ML Engineer specializing in AI SaaS, MLOps, and cloud infrastructure
“Built and shipped an AI-powered driver ranking/assignment system at AffirmoAI using LLM intent classification + RAG over pgvector/Postgres, served via FastAPI with a React UI that explains scores. Drove measurable improvements through optimization and iteration (latency down to <800ms, adoption 60%→90%+) and implemented rigorous eval loops with dispatcher ground truth plus cold-start handling for new drivers.”
Mid-level Software Developer specializing in microservices and AWS cloud-native systems
“Full-stack engineer focused on application-layer product work (70–75%), with production experience building real-time operational dashboards (React/TypeScript + Node/Express + WebSockets + Postgres) and measurable impact (50% reduction in data entry time). Also owned a Flask backend for a SaaS product with token auth/RBAC, versioning, observability, and performance tuning, and has operated containerized apps on AWS (EKS, RDS/Aurora, S3, API Gateway) including handling a real latency/scaling incident end-to-end.”
Mid-level Full-Stack Java Developer specializing in microservices and cloud-native systems
“Backend engineer with hands-on experience building real-time, event-driven systems at Walgreens, including a Kafka-based prescription status notification service and scalable pipelines for messy prescription/inventory data. Strong focus on reliability patterns (retries, idempotency, DLQs) and iterating based on pharmacist feedback to improve usability.”
Senior Full-Stack AI Engineer specializing in Generative AI and FinTech
“Backend engineer who built and owned an AI-powered financial research product end-to-end, using a typed NestJS/GraphQL backend with LangGraph-style agent routing to produce sourced, structured financial analysis. Emphasizes finance-grade correctness (Zod validation, metric registries, unit/empty-result guardrails) while keeping latency low via batching, caching, and fast token streaming, and has led incremental migrations using strangler/feature-flag/shadow traffic patterns.”
Junior Software Engineer specializing in full-stack web and cloud systems
“Co-op engineer at EnFi who built and maintained a multi-tenant prompt library and LLM workflow tooling used by internal teams and external enterprise clients. Led TypeScript/React package design and standardized a typed workflow abstraction across disparate implementations (React, Go, JSON), improving reliability and developer adoption. Delivered measurable performance gains (~25% latency reduction) and owned end-to-end execution including docs, demos, debugging, and deployment.”