Pre-screened and vetted.
Junior AI Full-Stack Engineer specializing in LLM automations and RAG systems
“Built and shipped a production LLM-powered customer support assistant using a Python/FastAPI backend with RAG (embeddings + vector search) over internal docs and product/operational data. Instrumented the system with logging/metrics and ran continuous eval loops; post-launch improvements focused on retrieval quality (chunking/ranking) and performance/cost tradeoffs (query classification, caching, validation guardrails).”
Mid-Level AI/Full-Stack Engineer specializing in conversational AI and SaaS products
Mid-level Full-Stack Software Engineer specializing in AI, data pipelines, and cloud-native apps
Mid-level DevOps Engineer specializing in AWS, Kubernetes, and CI/CD automation
“DevOps/cloud infrastructure engineer focused on AWS automation: built GitHub Actions/Jenkins pipelines for containerized deployments with strong security controls and rollback, and implemented Terraform-based AWS provisioning with modular code and remote state/locking. Has led on-prem to AWS migration cutovers with structured risk/rollback planning and stabilization, but has not worked directly with IBM Power/AIX/LPARs or PowerHA/HACMP.”
Mid-level DevOps Engineer specializing in cloud infrastructure and CI/CD automation
Mid-level Full-Stack Developer specializing in Python, React, and cloud-native microservices
Junior Full-Stack Software Engineer specializing in AI and web applications
“LLM/AI backend engineer with hands-on experience taking customer LLM prototypes into production using FastAPI, containerization, CI/CD, and OpenTelemetry-based observability. Demonstrated measurable impact by cutting LLM costs ~40% and reducing workflow errors ~50% through schema-enforced outputs, better tool definitions, retries, and prompt/model optimization; also supports pre-sales via technical discovery and rapid integration demos.”