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Vetted Databricks Professionals
Pre-screened and vetted.
Mid-level Data Analyst specializing in analytics, AI, and business intelligence
Mid-level Software QA Engineer specializing in web, API, and test automation
Senior Backend/Full-Stack Engineer specializing in cloud-native APIs and data platforms
Senior Machine Learning Engineer specializing in Generative AI and MLOps
CharanTeja Kurakula
Entry-Level AI Engineer specializing in NLP and LLM-powered applications
“AI engineer who built an agentic, production-deployed LLM workflow for tobacco violation parsing and automated multi-case creation, using six specialized agents and a human-in-the-loop confidence-threshold routing design. Addressed data privacy constraints by generating synthetic datasets with LLM prompting, and orchestrated reproducible end-to-end pipelines in LangChain with robust testing and evaluation (precision/recall, micro-F1).”
Utkarsh Vijayvergia
Entry-level Software Engineer specializing in full-stack, cloud, and AI systems
“Builder with hands-on experience shipping full-stack products across AWS cloud infrastructure, React/TypeScript apps, SQL-backed systems, and privacy-focused AI workflows. Stands out for combining cost-aware architecture, strong debugging instincts, and product thinking—from an e-commerce platform automated with IaC to a university admin portal serving 10,000+ users and a locally run AI assistant with configurable guardrails.”
Pavan Sai Reddy Pendry
Junior AI/ML Engineer specializing in GenAI, RAG, and full-stack ML systems
“Built a university campus assistant chatbot (BabyJ/WWJ) using RAG and agentic routing with a FastAPI + React stack and JWT auth, focusing heavily on production concerns like latency and reliability. Uses techniques like speculative prefetching, smart intent routing, and rigorous eval/testing (golden sets, regression, edge cases) while collaborating closely with campus admin/advising teams to iterate based on real user feedback.”
“LLM/RAG engineer at Connex AI who built and deployed a production healthcare agent to extract clinical insights from medical data/notes. Strong focus on real-world reliability—hallucination mitigation (citations, schema validation, confidence thresholds, rejection logic), custom LangChain orchestration (query rewriting, fallback paths), and production evaluation/observability—while collaborating closely with clinical SMEs to ensure clinical fit and time savings.”
Intern Data Scientist specializing in LLM agents, RAG, and real-time ML pipelines
Mid-Level Application Support Engineer specializing in SAP, cloud IAM, and production operations
Mid-level Full-Stack/AI Engineer specializing in LLM microservices, RAG, and data pipelines
Intern-level Business Analytics professional specializing in data science and BI
Mid-level Data Scientist specializing in ML, NLP, and Generative AI
Mid-level AI/ML Engineer specializing in fraud detection, credit risk, and NLP/RAG
Junior Data Analyst specializing in analytics engineering and forecasting
Mid-level AI Engineer specializing in LLM agents, RAG, and evaluation
Mid-level Data Engineer specializing in cloud-native batch and streaming pipelines
Mahaboob Johny
Mid-level Data Analyst specializing in SQL/Python analytics, ETL pipelines, and BI dashboards
“Data/AI practitioner who built a production LLM-driven healthcare claims analytics and dashboarding system to reduce avoidable ER visits—processing 1.4M+ claims, flagging 19% as non-emergent, and projecting ~$2.8M in annual savings. Demonstrates strong real-world LLM reliability and performance engineering (grounding, numeric validation, caching, materialized views, quantization) plus orchestration experience with Airflow and Azure Data Factory.”
Harshit Vashisth
Junior AI Engineer specializing in LLMs, RAG systems, and MLOps
“Robotics software engineer who built an end-to-end system ("justmatrix"), focusing on multi-agent orchestration and a multi-RAG retrieval backend/API. Has hands-on ROS experience, including a custom node for reliable high-frequency sensor data routing, plus deployment automation using Docker, Kubernetes, and CI/CD.”
Akash Parekh
Mid-level Full-Stack Developer specializing in React, Node.js, and cloud deployment
“Frontend engineer with experience building enterprise ERP/CRM dashboards in React + TypeScript, including cron-driven data updates and differentiated state flows. Emphasizes CI/CD pipeline setup, performance optimization (Core Web Vitals, React Profiler), and disciplined delivery practices (risk-based QA, phased rollouts); also has Figma-to-responsive implementation experience.”