Pre-screened and vetted.
Mid-level Cloud Platform Engineer specializing in AWS and Kubernetes
Senior Software Engineer specializing in cloud-native SaaS, IoT, and GenAI platforms
Senior Site Reliability Engineer specializing in multi-cloud DevOps and Kubernetes
Mid-level Full-Stack Developer specializing in FinTech and modern web platforms
Senior Full-Stack Engineer specializing in cloud-native microservices and AI solutions
Mid-level Backend Software Engineer specializing in cloud-native microservices and AI automation
Senior DevOps/SRE Engineer specializing in cloud infrastructure and CI/CD
Senior Site Reliability/DevOps Engineer specializing in AWS/Azure Kubernetes and CI/CD
Mid-level Full-Stack Developer specializing in cloud-native microservices
Senior DevOps/SRE Engineer specializing in multi-cloud infrastructure and Kubernetes
Mid-level Backend Software Developer specializing in cloud-native microservices
“Backend engineer with American Express experience maintaining an internal Python/Flask rewards simulation microservice used by product analysts and QA. Demonstrated strong performance and scalability work: moved batch simulations to Celery, added Redis caching to cut DynamoDB latency, and tuned Postgres/SQLAlchemy queries with EXPLAIN ANALYZE and composite indexes (bringing API responses under ~200ms by queueing jobs). Also has experience integrating ML via Flask-based model-serving APIs (scikit-learn/LightGBM packaged with joblib) and designing multi-tenant data isolation and tenant-specific configuration systems.”
Senior Software Engineer specializing in cloud-native microservices and secure enterprise platforms
“Full-stack engineer with strong production ownership in banking/identity & entitlements systems, building Spring Boot + Postgres/Redis services and React dashboards, then deploying on AWS EKS with Jenkins CI/CD. Demonstrated impact through reduced authorization latency and fewer access-related support tickets, plus strong observability and reliability practices (CloudWatch, tracing, autoscaling, Kafka pipelines with DLQs and reconciliation).”
Senior AI/ML & Full-Stack Engineer specializing in GenAI, RAG, and MLOps platforms
“Backend/data platform engineer who owned end-to-end production services for a fleet analytics/GenAI platform, spanning FastAPI microservices on Kubernetes and AWS (EKS + Lambda) event-driven workloads. Strong in reliability/observability (OpenTelemetry, circuit breakers, idempotency), data pipelines (Glue/Airflow/Snowflake), and measurable performance/cost wins (SQL 10s to <800ms P95; ~30% compute cost reduction).”
Mid-level Machine Learning Engineer specializing in safety-critical and uncertainty-aware ML systems
“Built and productionized an LLM-powered assistant for company documents and support questions, focused on reducing time spent searching PDFs/policies/tickets while preventing hallucinations by grounding answers in approved sources. Demonstrates strong production engineering (Kubernetes/orchestration, caching, monitoring, fallbacks) plus security-minded permissioning and close collaboration with operations/support stakeholders.”
Mid-Level Full-Stack Software Engineer specializing in distributed systems and cloud integrations
“Backend engineer with enterprise SaaS experience (Zoho) who owned an end-to-end cloud integration between Endpoint Central and ServiceDesk Plus, redesigning device onboarding across 64+ scenarios and building a fault-tolerant sync engine that recovered 100% failed transactions. Also built and operated production systems across the stack—FastAPI services with strong testing/observability, React+TypeScript portals, PostgreSQL performance tuning, and AWS deployments with real incident response (RDS CPU saturation resolved with zero downtime).”
Mid-Level Full-Stack Software Engineer specializing in cloud-native microservices and data pipelines
“Engineer with Deloitte experience building real-time analytics products and scalable Kafka/Go/Postgres pipelines, plus production LLM features using RAG and embeddings. Demonstrates strong focus on performance, reliability, and guardrails/evaluation loops to reduce hallucinations and improve real-world AI system quality.”
Junior Full-Stack Engineer specializing in TypeScript/React, Python, and AWS
“Full-stack engineer who built and owned an end-to-end real-time engineering dashboard for Medtronic robotic surgical systems, streaming high-frequency sensor/kinematic data via Python WebSockets to a React/TypeScript UI. Differentiates through performance/reliability practices (stable core vs experimental layer, observability, caching) and high-impact 3D visualization + session playback that became part of engineers' regular bench-testing workflows.”
Mid-Level Software Engineer specializing in cloud-native microservices and analytics platforms
“JavaScript engineer with a track record of diagnosing and fixing real performance issues end-to-end—profiled a charting library freeze on large datasets, rewrote layout logic to batch updates, added tests, and got the PR merged upstream. Also has experience stabilizing backend services in ambiguous, fast-moving projects by defining priorities, tightening API contracts, and owning delivery through deployment.”
Mid-level Full-Stack Developer specializing in web platforms and cloud (AWS)
“Full-stack engineer with financial services experience (Lincoln Financial) who owned a customer-facing financial portal end-to-end using TypeScript/React and Node/Express. Has hands-on microservices and RabbitMQ event-driven workflows, addressing scale issues like retries/duplicates with idempotency and traceable logging, and built an internal real-time ops/support dashboard to improve monitoring and incident response.”
Mid-Level Software Developer specializing in full-stack, cloud-native microservices and AI integrations
“Backend/AI engineer who has built production Spring Boot APIs on AWS (JWT auth, Redis/MySQL) and solved a real-world silent data integrity issue by implementing idempotency keys plus DB constraints/transactions. Also shipped an LLM-based document Q&A feature using a RAG pipeline with evaluation + human review, and designed multi-step agent workflows with verification, retries, and escalation guardrails.”
Senior Software Engineer specializing in cloud-native microservices and AI-enabled platforms
“Infrastructure/operations engineer with hands-on production IBM Power/AIX (AIX 7.x, VIOS, HMC) and PowerHA/HACMP clustering experience, including DLPAR changes, failover testing, and incident recovery. Also delivers modern cloud DevOps work—GitHub Actions CI/CD for Docker-to-Kubernetes on AWS and Terraform-based provisioning of core AWS infrastructure (VPC/EKS/RDS/IAM) with controlled rollouts and drift checks.”
Mid-level DevSecOps/Cloud Engineer specializing in AWS platform engineering and Kubernetes
“Infrastructure/Platform engineer with deep production ownership of large IBM Power/AIX estates (70 LPARs, dual VIOS, HMC across two data centers), including live DLPAR tuning and PowerHA clustering for Oracle/WebSphere. Also brings modern DevOps/IaC experience—built GitHub Actions pipelines deploying to Kubernetes with OIDC/Vault secrets and implemented Terraform to provision AWS EKS/VPC/IAM/ALB/RDS with drift detection and controlled rollouts.”
Intern Software Engineer specializing in cloud infrastructure and Kubernetes