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Vetted Llama Professionals
Pre-screened and vetted.
Mid-level Agentic AI Engineer specializing in autonomous LLM and RAG systems
Mid-Level Full-Stack Software Engineer specializing in cloud-native microservices and FinTech
Senior Software Developer specializing in cloud-native microservices and GenAI/ML
Mid-level AI/ML Engineer specializing in Generative AI agents and workflow automation
Mid-level AI/ML Engineer specializing in LLM fine-tuning and RAG for healthcare
Mid-level Full-Stack AI Engineer specializing in agentic SaaS and LLM systems
Dhananjay Dubey
Senior Full-Stack Game Engineer specializing in multiplayer Unity and mobile systems
“Unity/C# game developer with hands-on experience shipping large-scale multiplayer mobile games, including titles cited at 1M+ and 10M+ downloads. Combines real-time networking and physics optimization expertise with AI/MR research experience, including an IEEE-published sports coaching system using pose estimation, SMPL-X, and LSTM models. Particularly strong in latency-sensitive, cross-platform interactive systems spanning mobile, multiplayer, and mixed reality.”
Yashwanth Penugonda
Mid-level AI/ML Engineer specializing in LLMs, RAG, and production GenAI systems
“Built and deployed a production LLM-powered RAG knowledge system to unify operational/policy information across PDFs, wikis, and databases, emphasizing auditability and low-latency/cost performance. Improved answer relevance at scale by moving from pure vector search to hybrid retrieval with metadata filtering and reranking, and partnered closely with healthcare operations/compliance to define acceptance criteria and human-in-the-loop guardrails.”
Kalyani sai laxmi pallavi lakkoju
Mid-level Data Analyst specializing in BI, supply chain, and AI analytics
“Analytics-focused candidate with hands-on experience in both supply chain data and AI product analytics. They have built SQL and Python pipelines for messy ERP/inventory data as well as high-volume user event data, and have driven experimentation, retention measurement, and dashboarding for AI avatar and voice/image cloning features.”
Mid-level Data Scientist & AI Engineer specializing in NLP, computer vision, and MLOps
Tarun Gowda
Mid-level AI Engineer specializing in Generative AI and multimodal RAG
“Full-stack engineer who helped build and launch an internal genAI platform called GAIL, supporting multiple LLMs, confidential document upload for RAG pipelines, and collaborative chat. Worked across FastAPI, React/TypeScript, AWS/DynamoDB, and Azure, with notable ownership of backend RAG logic, MCP integration architecture, and frontend fixes that improved chat usability.”
Atharva Joshi
Mid-level GenAI Engineer specializing in RAG systems and AI agents
“LLM/agentic systems builder who has deployed production solutions for a resource management firm, using an MCP-driven architecture with Neo4j + Elasticsearch and a ChatGPT frontend to generate candidate/company “SmartPacks” and answer entity Q&A. Also built a LangGraph/LangSmith-orchestrated multi-agent workflow that automates data-infra change requests end-to-end (impact analysis, SQL + tests, and PR creation), and delivered a ~60% latency reduction through TTL-based context caching while improving accuracy via a business data dictionary.”
Junior Full-Stack Software Engineer specializing in cloud-native microservices and data platforms
Senior QA Automation Engineer specializing in test automation and end-to-end web testing
Mid-level AI/ML Engineer specializing in cloud-native data pipelines and RAG systems
Mid-level Machine Learning Engineer specializing in LLMs, RAG, and MLOps
Tanweer Ashif
Mid-level AI/ML Engineer and Data Scientist specializing in LLMs and MLOps
“Data science/AI intern at University at Buffalo Business Services who built and deployed production systems spanning classic ML and LLM assistants. Delivered real-time competitor intelligence for a Cornell-partnered, $1B beverage launch by scraping/cleaning 5,000+ SKUs and deploying models via API, then built a domain-aware LLM assistant to modernize Excel-based workflows with strong grounding, privacy controls, and sub-5s latency.”