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Vetted AWS Glue Professionals
Pre-screened and vetted.
Mid-level AI/ML Engineer specializing in fraud detection, credit risk, and NLP/RAG
Entry-level Machine Learning Engineer specializing in LLMs, RAG, and data pipelines
Junior Data Analyst specializing in analytics engineering and forecasting
Mid-level Software Engineer specializing in Generative AI and cloud-native microservices
Mid-level Java Full-Stack Developer specializing in cloud microservices and AI/ML integration
Mid-level AI/ML Engineer specializing in fraud detection, credit risk, and NLP
Mid-level AI/ML Engineer specializing in Generative AI, NLP, and RAG systems
Haeshitha Indukuri
Entry AI/ML Engineer specializing in Generative AI, LLMs, and MLOps
“Built and productionized a MediCloud/Medicoud LLM microservice platform that lets clinicians query medical data in natural language, orchestrating multi-step RAG-style workflows with LangChain and evaluating/debugging with LangSmith. Delivered measurable gains (consistency ~70%→90% / +20%; latency ~2.0s→1.1s / -40%) by implementing structured prompts, fallback logic across multiple LLMs, hybrid retrieval tuning, and AWS Lambda performance optimizations (package size, async, caching).”
Mahaboob Johny
Mid-level Data Analyst specializing in SQL/Python analytics, ETL pipelines, and BI dashboards
“Data/AI practitioner who built a production LLM-driven healthcare claims analytics and dashboarding system to reduce avoidable ER visits—processing 1.4M+ claims, flagging 19% as non-emergent, and projecting ~$2.8M in annual savings. Demonstrates strong real-world LLM reliability and performance engineering (grounding, numeric validation, caching, materialized views, quantization) plus orchestration experience with Airflow and Azure Data Factory.”
kireeti Sangarsh
Mid-level Data Engineer specializing in cloud ELT pipelines and analytics engineering
“Data engineer who has owned end-to-end ELT pipelines on Airflow + AWS (S3/Glue/Lambda) with Snowflake/Redshift, processing millions of records per day and tens of GBs via PySpark. Built strong data quality and reliability practices (40% quality improvement, 99%+ uptime), and also designed a resilient web-scraping system with anti-bot defenses and schema-change versioning plus REST APIs for serving curated data.”
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 Full-Stack Software Engineer specializing in cloud microservices and data/ML
Senior AI/ML Engineer specializing in NLP, LLMs, speech, and computer vision
Senior AI/ML Engineer specializing in NLP, LLMs, speech, and computer vision
Senior AI/ML Engineer specializing in NLP, LLMs, speech, and computer vision
Andrew Fu
“Backend/infrastructure engineer in the EBS org focused on global server lifecycle and fleet reliability. Led a major modernization from manual, ticket-driven recovery to centralized Python services and operator tooling with DynamoDB-backed state, strong auth/allowlisting, and CloudWatch monitoring, plus an AWS Glue/S3/SNS data pipeline to join server and hardware datasets for global operational querying and automated recovery.”