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Vetted Azure Synapse Analytics Professionals
Pre-screened and vetted.
Mid-level AI/ML Engineer specializing in LLMs, RAG, and cloud AI infrastructure
Mid-level Data Scientist specializing in Healthcare ML and Generative AI
Mid-level ML Engineer specializing in FinTech risk, fraud, and GenAI RAG systems
Mid-level Data Scientist specializing in ML, NLP and forecasting
Mid-level Data Scientist specializing in Healthcare ML and Generative AI
Junior Generative AI Engineer specializing in LLM fine-tuning and RAG pipelines
Mid-level Data Engineer specializing in AI, analytics, and cloud data platforms
Junior Data Analyst specializing in SQL, Python, and BI analytics
Mid-level Software Engineer specializing in data platforms, cloud, and AI
Mid-level AI/ML Engineer specializing in LLMs, RAG, and agentic AI systems
Intern Data Scientist / ML Engineer specializing in predictive modeling and data pipelines
Mid-level AI/ML Engineer specializing in MLOps, streaming data, and NLP/CV
Mid-level SQL Developer specializing in MySQL, ETL, and cloud data pipelines
Pranava Reddy Kothapally
Junior Data Engineer specializing in Azure, CRM data pipelines, and marketing personalization
“LLM/AI engineer who has deployed production RAG conversational analytics and Text-to-SQL systems over Snowflake and curated data marts, emphasizing enterprise-grade guardrails for accuracy, security, and cost. Notable for a structured approach to reducing hallucinations (curated metric/table registry, SQL validation, RBAC, and citation-backed responses) and for building resilient, observable multi-step agent workflows using LangChain/LlamaIndex and Airflow.”
Ajith Kumar
Mid-level AI Data Engineer specializing in GenAI, RAG, and cloud data pipelines
“LLM/agentic AI builder who deployed a production ITSM automation agent on Google ADK integrating ServiceNow and FreshService, with strong safety guardrails (human-approval gating and runbook-only command execution) and rigorous evaluation (500 synthetic tickets; 80%+ false-positive reduction). Also partnered with finance to deliver an AI agent that automated invoice/SOW retrieval and monthly reporting to account managers, reducing manual back-and-forth.”
Lakshmi Swathi Sreedhar
Mid-level AI Engineer specializing in Generative AI and LLM systems
“Built and deployed a production-grade, multi-agent Text-to-SQL assistant that lets non-technical stakeholders query large enterprise databases in natural language. Uses Pinecone-based schema retrieval + LLM reasoning (Gemini/Claude/GPT) with a dedicated validation agent (schema/syntax checks and safe dry runs) to reduce hallucinations and improve reliability, while optimizing latency and cost via async execution and embedding caching.”
Vengalarao Pachava
Junior AI Data Engineer specializing in Azure Databricks lakehouse and GenAI RAG systems
“Backend/applied AI engineer from Cloud Rack Systems who built production GenAI/RAG and data platforms on Azure/Databricks at enterprise scale (2.5M records/day). Known for making LLM systems behave like deterministic services via strict retrieval contracts, citation-based validation, and strong observability—shipping a knowledge assistant used daily by 50+ users while driving hallucinations near zero and materially improving latency and cost.”