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Vetted Transformers Professionals
Pre-screened and vetted.
Mid-level AI Engineer specializing in NLP, LLM fine-tuning, and RAG systems
Mid-level Data Engineer and AI Engineer specializing in LLMs and data platforms
Junior Software Engineer specializing in backend systems, AI agents, and EdTech platforms
Junior Machine Learning Engineer specializing in LLM agents, knowledge graphs, and multimodal AI
Mid-level AI Engineer specializing in LLM automation and RAG systems
Junior Machine Learning Engineer specializing in deep learning and healthcare AI
Intern Data Scientist / ML Engineer specializing in predictive modeling and data pipelines
Junior AI/ML Engineer specializing in RAG and multi-agent LLM systems
Mid-level AI/ML Engineer specializing in GenAI, RAG, and multi-agent LLM systems
Mid-level Full-Stack AI Engineer specializing in agentic RAG and LLM fine-tuning
Senior Systems Integration Engineer specializing in industrial automation and power systems
Mid AI/ML Engineer specializing in LLMs, MLOps, and FinTech analytics
Naveen Kancharla
Mid-level AI & Backend Engineer specializing in RAG systems and scalable APIs
“Built and deployed a production LLM-powered document Q&A system using a strict RAG pipeline (LangChain-style orchestration + FAISS) to help users query large internal document sets. Demonstrates strong reliability focus through hallucination mitigation, curated offline evaluation with grounding checks, and production monitoring (latency/fallback rates) plus stakeholder alignment via demos and business metrics.”
Swarag Reddy Pingili
Junior AI/ML Software Engineer specializing in LLM agents and RAG systems
“AI/back-end engineer at Canon who helped build and operate an internal production LLM platform that acts as a secure middle layer between users and models, defending against jailbreaks/prompt injection while enabling RAG, memory, and grounded responses over company data. Experienced with LangChain/LangGraph orchestration, vector DB retrieval, and reliability practices (testing, monitoring, adversarial prompts) to run high-throughput, low-latency AI workflows in production.”
Snigdha Reddy Podduturi
Junior Data & AI Engineer specializing in cloud AI and analytics
“Built production AI backend systems in healthcare and e-commerce, including a healthcare agent that automated clinical workflows like medication refills, immunizations, and scheduling using FHIR APIs and cloud-native infrastructure. Strong in end-to-end backend ownership, LLM orchestration, and adding guardrails/validation for high-stakes and customer-facing AI workflows.”
Swapnil Ramanna
Mid-level Data Scientist specializing in Generative AI and Healthcare Analytics
“Built a LangGraph-based, tool-routing LLM chatbot to deliver fast, trustworthy investment-stock insights (including tariff impact) and deployed it to production on Snowflake after initially developing in Azure with AI Search and the Microsoft Agent Framework. Improved routing robustness by moving from LLM-based decisions to a deterministic router backed by schema-relationship graphs and YAML metadata, and ran the project iteratively with non-technical stakeholders over an 8-month engagement.”
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.”