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Vetted Full-Stack Development Professionals
Pre-screened and vetted.
Mid-level Solution Architect specializing in government and FinTech systems
Mid-level Full-Stack Software Engineer specializing in distributed systems and cloud platforms
Mid-level Backend Software Engineer specializing in distributed systems and payments
Senior Full-Stack AI Engineer specializing in LLMs, RAG, and healthcare AI
Mid-level Full-Stack Engineer specializing in cloud-native web applications
Executive Full-Stack Engineer specializing in marketplace, healthcare, and AI products
Junior Software Engineer specializing in cloud infrastructure and database tooling
Intern AI/ML Engineer specializing in generative AI and multimodal agentic systems
Senior AI/ML Engineer specializing in LLM systems and conversational AI
Director-level product engineering leader specializing in enterprise cloud transformation
Senior Software Engineer specializing in full-stack, data engineering, and AI/ML
Executive product leader specializing in enterprise platforms across healthcare and FinTech
Junior AI Engineer specializing in enterprise LLM and FinTech systems
Senior Software Engineer specializing in full-stack SaaS, AI workflows, and FinTech
Principal software engineer and technical founder specializing in AI platforms
Mahesh Purushothaman
Senior Director of Software Engineering specializing in cloud-native microservices for streaming platforms
“Engineering leader who drove TiVo IPTV’s client-facing API modernization from a monolith to AWS-based microservices (API Gateway, Lambda, EKS, Kafka, DynamoDB/RDS), including phased/blue-green production routing of millions of calls. Emphasizes org scaling through skill-based hiring, mentorship, and a you-build-you-run ownership culture, while balancing technical leadership with executive stakeholder communication and budgeting.”
Lalithya Manasa Patri
Senior Data Engineer specializing in cloud ETL and real-time streaming pipelines
“Data engineer with eBay experience owning end-to-end pipelines for real-time order and user behavior analytics at 10M+ records/day. Strong in PySpark/SQL transformations, Airflow reliability patterns, and production observability (CloudWatch), with measurable outcomes including improved data quality and 30–40% query performance gains. Also built Python data APIs for analytics/ML consumers with versioning and backward compatibility.”