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Vetted AWS Step Functions Professionals
Pre-screened and vetted.
Junior Full-Stack Engineer specializing in AI-enabled web apps and AWS serverless systems
Senior Full-Stack Java Engineer specializing in cloud-native microservices and GenAI
Senior Backend/Full-Stack Developer specializing in AWS serverless microservices
Senior Backend Developer specializing in AWS serverless and Python ETL
Mid-level Full-Stack Java Developer specializing in Healthcare IT and FinTech
Mid-Level Full-Stack Software Engineer specializing in Java/Spring and AWS serverless
Mid-level Backend & Blockchain Developer specializing in Web3 and cloud-native systems
Senior Software Engineer specializing in backend, AWS cloud infrastructure, and data pipelines
Junior XR/VR Developer specializing in Unity multiplayer networking and cloud rendering
Junior Full-Stack AI Developer specializing in multi-agent LLM systems on AWS
Intern AI/ML Engineer specializing in NLP, graph analytics, and agentic RAG systems
Staff/Lead DevOps & Site Reliability Engineer specializing in cloud infrastructure and Kubernetes
Senior Full-Stack AWS Developer specializing in cloud-native microservices and serverless systems
Ricky Zheng
Senior Backend/AI Engineer specializing in AWS-native data processing and legacy modernization
“Backend/data engineer with hands-on production experience building a FastAPI Python service on AWS for real-time AI workflows (Postgres/Redis, containers behind API Gateway) with strong reliability practices (JWT auth, timeouts/retries, health checks). Has delivered AWS infrastructure using Terraform + GitHub Actions across environments, built Glue ETL pipelines into Snowflake with idempotent recovery, and modernized legacy batch workflows via parallel-run parity validation and phased cutovers.”
Mid-level Python Developer specializing in cloud-native APIs and microservices
Anjali Chepuri
“Built and deployed an LLM-powered financial document processing and summarization platform at Morgan Stanley using a production RAG pipeline (PDF ingestion, embedding-based retrieval, schema-constrained JSON outputs) delivered via FastAPI microservices on Kubernetes. Drove measurable impact (40% reduction in manual review time) and improved factual accuracy for numeric fields by 30% through metadata-aware retrieval, strict schemas, and post-generation validation, with a human feedback loop from financial analysts.”