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Vetted Data Engineering Professionals
Pre-screened and vetted.
Ravikanth Kasamsetty
Executive AI/ML Engineering Leader specializing in cloud-native SaaS and GenAI platforms
“Engineering leader who modernized and unified a fragmented product suite at Milestone via a multi-year cloud-native roadmap, delivering an MVP in three quarters and boosting team velocity by 40% through cross-functional squads. At Prometheum, led a trust-building hybrid architecture (AWS control plane + customer-hosted data plane) using Kubernetes to ensure sensitive enterprise data never left customer networks while remaining cloud-agnostic across providers.”
Subhash Mothukuru
Mid-level Machine Learning Engineer specializing in LLMs, generative AI, and MLOps
“Built and shipped a production LLM-powered medical scribe that generates structured clinical visit summaries using RAG, strict JSON schemas, and post-generation validation to reduce hallucinations. Experienced in making LLM workflows deterministic and observable (structured logging/metrics/tracing) and in evaluation-driven iteration with metrics like schema pass rate and edit rate; collaborated closely with clinicians and policy stakeholders at Scale AI to drive adoption.”
Sahil Bansal
Mid-level Backend & ML Engineer specializing in LLM systems and scalable AI pipelines
“Built and shipped a real-time AI phone agent for small businesses that handles bookings/FAQs/messages using streaming ASR, an LLM with tool-calling, and TTS; deployed to production for multiple paying customers. Demonstrates strong applied LLM reliability practices (tool-first grounding, retrieval, hard-negative testing, and production monitoring) and experience orchestrating multi-step AI workflows with Airflow, Prefect, and AWS Step Functions.”
Kamal Basha
Executive Data & AI Product Leader specializing in GenAI/LLM and SaaS platforms
“Technology/engineering leader with experience at Real Messenger, Wolters Kluwer, and Accenture AI, spanning roadmap definition through execution and org scaling. Has operated at the executive level (fundraising, investor relations, SPAC merger activities, media presentations) while driving architecture decisions validated by PoC/testing/production success metrics.”
Executive Engineering Leader specializing in Blockchain, FinTech, and SaaS platforms
Executive Engineering Leader specializing in distributed systems, cloud platforms, and AI
Executive CTO and Product Engineering Leader specializing in cybersecurity, data platforms, and AI
Mid-level Software Engineer specializing in backend and AWS cloud infrastructure
Mid-level Data Scientist specializing in NLP, MLOps, and semiconductor manufacturing analytics
Intern Machine Learning & Cloud Engineer specializing in cloud-native deployment and forecasting
Mid-level Machine Learning Engineer specializing in MLOps and cloud-native ML systems
Mid-level AI/ML Engineer specializing in LLMs, RAG pipelines, and multi-agent systems
Staff Software Engineer specializing in AI/ML and data engineering for healthcare automation
Mid-level Software Engineer specializing in Python, ML/LLM systems, and scalable microservices
Director of Engineering specializing in AI, data platforms, and cloud cost optimization
Senior AI/ML Software Engineer specializing in LLMs, NLP, and scalable ML platforms
Junior AI/ML Engineer specializing in LLM agents, RAG, and multimodal data pipelines
Mid-level Data Scientist / GenAI & ML Engineer specializing in LLMs, RAG, and recommendations
Intern Software Engineer specializing in data engineering and LLM evaluation
Executive Platform & Infrastructure Engineering Leader specializing in FinTech SaaS, Cloud, Data & AI
Senior AI/ML Engineer & Data Scientist specializing in NLP, entity resolution, and knowledge graphs
Mid-level Machine Learning Engineer specializing in LLMs, ranking, and scalable ML systems