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Vetted Amazon Redshift Professionals
Pre-screened and vetted.
Mid-level AI/ML Engineer specializing in GenAI, LLMs, and RAG pipelines
Mid-level Machine Learning Engineer specializing in fraud prevention and LLM systems
Principal Data Scientist specializing in Generative AI and MLOps
Staff Software Engineer specializing in cloud, networking, and distributed systems
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
Mid-level Data Engineer specializing in cloud lakehouse platforms (Azure/AWS/Snowflake)
Senior Software Engineer specializing in cloud-native healthcare and financial services
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
Senior Software Engineer specializing in data engineering, BI analytics, and AI/ML
Surya Singh
Mid-level AI/ML Engineer specializing in FinTech and fraud detection
“ML/backend engineer with PayPal experience building high-stakes production systems, including a GenAI internal support assistant and a real-time fraud scoring pipeline. Strong in Python/FastAPI, model-serving infrastructure, RAG architecture, and production observability, with clear readiness to transition those backend patterns into a TypeScript stack.”
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.”
Vikas Ravula
Senior Data Engineer specializing in cloud data platforms and real-time streaming for financial services
“Data engineer with experience at Bloomberg, UBS, and Bank of America building high-volume financial data platforms and services. Owned an end-to-end pipeline processing ~150–200M records/day (Kafka/Cassandra/S3 → Spark/PySpark → Snowflake) with strong data quality controls and Airflow reliability practices, reporting ~99% reliability and major performance gains. Also built large-scale external API ingestion with compliance-minded rate limiting, schema versioning, and quarantine/validation layers.”
Sriram Rajaraman
Senior Infrastructure Platform Architect specializing in Kubernetes and hybrid cloud
“Platform/infra engineer with strong ownership of Kubernetes on VMware and day-to-day hybrid on-prem-to-AWS operations. Has hands-on experience automating infrastructure delivery with Terraform/Ansible/CI-CD, and has resolved real production issues spanning CSI storage reattachment during upgrades, vSphere storage-latency performance degradation, and hybrid connectivity/routing failures with improved validation, monitoring, and failover.”