.png){kind=logo}
Vetted Amazon Redshift Professionals
Pre-screened and vetted.
Mid-level AI/ML Engineer specializing in RAG, NLP, and MLOps
Brian Sanders
Senior Backend Engineer specializing in GenAI, LLMs, and scalable data pipelines
“Backend/ML platform engineer from Snapsheet who owned production Python services and data pipelines for insurance claims, including an AI document classification/summarization FastAPI service on ECS/Fargate processing 1M+ documents/year. Strong in AWS infrastructure (Terraform, CI/CD, secrets/IAM, autoscaling), Glue/PySpark ETL with schema evolution controls, and legacy SAS-to-microservices modernization with safe, feature-flagged rollouts and measurable performance wins.”
Akhil Maram
Senior Data Engineer specializing in real-time data platforms and lakehouse architectures
“Senior, product-focused engineer who has built real-time customer-facing web applications and a microservices backend (TypeScript/React/Node) using RabbitMQ, MongoDB, and Redis. Demonstrates strong operational maturity (idempotency, tracing/observability, backpressure) and built an internal console that became the primary tool for debugging, replaying jobs, and managing system behavior.”
Shiva Arcot
Director of Security & Data Platform Engineering specializing in AI-driven cloud security
“Player-coach engineering leader focused on scalable data security scanning and risk detection in hybrid cloud, owning architecture and core implementation of an incremental/parallel DSPM scanning engine. Shipped production improvements including 60% lower scan latency and 30% fewer false positives, with strong emphasis on correctness under concurrency, multi-tenant observability (SLOs/burn-rate alerts), and disciplined rollout practices (feature flags, shadow scans, canaries).”
Director-level Backend & Data Engineering Leader specializing in AWS serverless platforms
Senior Full-Stack Software Engineer specializing in cloud-native microservices and AI platforms
Principal Data Scientist specializing in ML, NLP, and forecasting for marketing and supply chain
Staff Software Engineer specializing in commerce, checkout, and payments platforms
Staff Platform Architect specializing in distributed systems and enterprise architecture
Staff Full-Stack Engineer specializing in data engineering and real-time event platforms
Staff Full-Stack & Platform Engineer specializing in cloud-native distributed systems
Mid-level Software Engineer specializing in backend, ML platforms, and FinTech
Senior AI Engineer specializing in LLM systems and scalable backend platforms
Senior Full-Stack Software Engineer specializing in large-scale streaming platforms
Mid-level Machine Learning Engineer specializing in generative AI, NLP, and MLOps
Senior Machine Learning Engineer specializing in GenAI, NLP, and recommendation systems
Kanaad Deshpande
Intern Software Engineer specializing in distributed systems and cloud infrastructure
“Built and operated a production warehouse metadata collection platform at Sigma Computing, integrating Go/gRPC services with a TypeScript backend and MySQL, with strong emphasis on idempotency, retries, bounded-concurrency job queues, and Datadog-based observability. Also created Kurral (kurral.com), an AI agent runtime security and observability/governance SDK/proxy concept, iterating via pilot-customer feedback and market research; targeting founding engineer roles with $180–200k base and ~2–5% equity.”
SOURABH MISHRA
Senior Software Engineer specializing in FinTech and distributed systems
“Backend/AI engineer who has built a rule-service platform on AWS and evolved it into an agentic RAG system using LangChain, ReAct, tool calling, and LLM-as-judge review. Notable for combining heavy AI-assisted development with production safeguards like manual CR, CloudWatch monitoring, fallback strategies, benchmark testing, and user-feedback-driven model improvement.”
Sahil Sinha
Mid-Level Software Engineer specializing in full-stack development, cloud, and data infrastructure
“Software engineer at Fannie Mae (~3 years) working on high-volume loan data pipelines using AWS (SQS/S3), Java listeners, Postgres, and Python/SQL-based data quality validation. Also built a chess data collection system (leveraging experience as an International Master) with robust retry/monitoring, schema-change handling, and idempotent backfills to prevent bad data from reaching downstream systems.”