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Vetted AWS Glue Professionals
Pre-screened and vetted.
Senior Financial Analyst specializing in FP&A, cloud FinOps, and financial analytics
Mid-level Business Analyst specializing in data analytics and financial systems
Senior Software Engineer specializing in AI-native backend platforms for Healthcare and FinTech
Mid-level Data Engineer specializing in cloud data platforms and streaming pipelines
Mid-level Software Engineer specializing in AWS backend systems and LLM infrastructure
Senior Technology Consultant specializing in cloud, data engineering, and AI solutions
Mid-level Generative AI & Machine Learning Engineer specializing in LLMs and RAG
Mid-level Full-Stack Software Engineer specializing in distributed systems and GenAI platforms
Mid-level Data Engineer specializing in cloud-native big data pipelines and analytics
Senior Machine Learning Engineer specializing in LLMs and Generative AI
Senior Data Engineer specializing in cloud data platforms and real-time analytics
Senior Backend Software Engineer specializing in AWS serverless and data pipelines
Senior Backend Engineer specializing in Python and cloud data platforms
Senior Full-Stack Engineer specializing in AI, cloud, and enterprise platforms
Intern Software Engineer specializing in full-stack, cloud, and AI systems
Chris Michaelson
Executive engineering leader specializing in cloud platforms, DevOps, and enterprise modernization
“Senior engineering leader with experience across cybersecurity, retail commerce, consulting, and media platforms, combining large-scale org leadership with hands-on architecture depth. Notable for driving measurable cloud modernization outcomes—multi-million-dollar cost savings, major latency and MTTR reductions, and compliance-heavy transformations—while also leading AI/NLP and consumer product simplification initiatives.”
Andrew Fares
Mid-level Data Engineer specializing in AI, GenAI, and cloud data platforms
“Built production AI systems inside AWS finance/procurement, including an LLM-based supplier quote classification and price-vetting workflow that drove $5M in savings over 3 months. Combines GenAI evaluation expertise, internal platform design, and reusable Python data-quality tooling with strong cross-functional execution across finance, accounting, and hardware engineering.”
Alexander Choy
Director of AI/ML Engineering specializing in MLOps, data platforms, and 3D computer vision
“Backend/data engineer focused on production ML/LLM systems: built a real-time FastAPI inference API on Kubernetes with strong reliability patterns (timeouts, idempotent retries, centralized error handling). Delivered AWS platforms using EKS + Lambda with GitHub Actions/Helm CI/CD and built Glue-based ETL from S3/Kafka into Snowflake with schema evolution and data-quality controls; also modernized legacy analytics/recommendation workflows into Python services with safe, feature-flagged cutovers.”
Ritesh Somashekar
Mid-level AI & ML Engineer specializing in NLP, LLMs, and scalable ML systems
“AI/ML engineer with experience spanning Accenture healthcare NLP systems, academic research, and Apple on-device LLM integration. Stands out for owning regulated production pipelines end-to-end—from HIPAA-compliant clinical NLP and EHR integrations to incident prevention, experiment tracking, and optimized on-device inference with LLaMA 3.”
Tanmayee Chandanam
Mid-level Data Scientist specializing in recommender systems, NLP, and real-time ML pipelines
“AI/LLM engineer who built and productionized an internal RAG-based knowledge system that ingests diverse sources (PDFs, Markdown, Slack), scaled retrieval with distributed FAISS and parallel ingestion, and reduced hallucinations via re-ranking, grounding prompts, and post-generation validation. Also has hands-on orchestration experience with Airflow and Kubernetes for reliable ETL/model pipelines, monitoring, and staged rollouts; reports ~15% accuracy improvement and adoption as the primary internal knowledge tool.”