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Vetted Amazon Redshift Professionals
Pre-screened and vetted.
Mid-Level Software Development Engineer specializing in AWS serverless, security, and ML platforms
Mid-level Machine Learning Engineer specializing in recommender systems and LLM/RAG pipelines
Mid-level AI/ML Engineer specializing in GenAI, LLMs, and RAG pipelines
Mid-level Machine Learning Engineer specializing in fraud prevention and LLM systems
Senior Data Engineer specializing in multi-cloud data platforms and pipelines
Technology Executive specializing in AI-native engineering and cybersecurity governance
Mid-level Data Engineer specializing in ML, LLM pipelines, and analytics platforms
Mid-level AI/ML Data Engineer specializing in data pipelines, MLOps, and LLM/RAG systems
Mid-level Machine Learning Engineer specializing in MLOps and scalable ML pipelines
Executive Data & AI Leader specializing in enterprise data platforms and multi-cloud transformation
Executive Engineering Leader specializing in AI automation and cloud platforms
Senior Data/GenAI Engineer specializing in cloud-native ML, RAG, and real-time data platforms
Senior Full-Stack Software Engineer specializing in scalable microservices and cloud platforms
Nehal Mahankali
Mid-level Full-Stack Python Developer specializing in cloud-native banking applications
“Backend engineer who built a low-latency real-time transaction API in Python/Flask, with strong depth in PostgreSQL/SQLAlchemy performance tuning (time-based partitioning, indexing, connection pooling). Has production experience integrating ML scoring and OpenAI-style APIs with safety/latency controls, and designing multi-tenant isolation strategies including per-tenant pooling/caching and premium-tenant isolation.”
Aleric Patterson
Senior Backend/Platform Engineer specializing in Python and AWS
“Backend/data engineer with hands-on production experience across Python/FastAPI services and AWS (Lambda, API Gateway, SQS, ECS) delivered via Terraform and GitHub Actions. Built Glue-to-Redshift ETL pipelines with Step Functions retry/catch patterns, schema evolution safeguards, and data quality checks; also modernized a legacy SAS monthly reporting system into Python microservices with rigorous side-by-side parity validation. Demonstrated strong SQL tuning skills with a reported improvement from 5 minutes to 15 seconds.”
Travis Johnson
Senior Full-Stack Software Engineer specializing in FinTech payments and fraud systems
“Backend/data engineer with production experience building credit/fraud enrichment services and checkout pipelines on AWS (EKS + Lambda) using FastAPI, Kafka, Postgres, and Redis, with a strong focus on reliability patterns (timeouts/retries/circuit breakers) and observability. Has also built AWS Glue/PySpark ETL into S3/Redshift with schema evolution and data quality controls, and modernized legacy credit decisioning into Java/Node microservices with parallel-run parity validation and feature-flag rollouts.”
Mid-level Full-Stack Python Engineer specializing in cloud-native payments and data pipelines
Mid-level Machine Learning Engineer specializing in MLOps, computer vision, and generative AI
Senior Python AI/ML Engineer specializing in MLOps, data engineering, and LLM applications