Vetted AI Engineers in California

“Robotics software engineer in an Autonomous Vehicle Lab building an end-to-end ROS 2 autonomous golf cart stack (sensor integration, SLAM, planning, and camera+LiDAR perception). Demonstrated strong systems-level debugging by fixing a FastLIO2 LiDAR timestamp/IMU-window issue that restored mapping quality, and stabilized real-time GigE camera perception by diagnosing backpressure and tuning ROS 2 QoS plus compressed transport.”

“AI/LLM engineer who built a production autonomous GenAI content ecosystem that generates short-form scripts, extracts viral highlights from long-form video, and dubs content into 33+ languages. Focused on making LLM outputs production-safe via schema enforcement, token-to-time alignment, critic-agent verification, and scalable async orchestration—cutting manual workflows by ~90% and saving $200k+ annually.”

“AI engineer who built and shipped a production AI document-understanding/search system at Sumeru Inc, including a full RAG + LLMOps evaluation stack (MLflow, DeepEval, RAGAS) deployed on GCP. Also developed LangChain/LangGraph multi-agent workflows for UAV flight-log analysis and has experience presenting AI solutions to non-technical stakeholders and prospect clients to drive POCs.”

“Built and shipped production RAG/agentic systems in high-stakes domains (biomedical and legal), including an enterprise biomedical document retrieval platform over ~10k scientific docs and a multilingual African-law assistant at the World Bank. Deep hands-on experience with LangChain/LangGraph/LlamaIndex and evaluation tooling (LLM-as-a-judge, safety/hallucination detection), with measurable gains in retrieval quality and hallucination reduction.”

“Built and productionized an agentic LLM workflow during a summer internship to transform unstructured clinical reports into analytics-ready structured data, using a LangChain multi-agent design plus an LLM-as-a-judge layer to control quality in a regulated setting. Also has experience orchestrating ML pipelines at Piramal Capital using AWS Step Functions/EventBridge/CloudWatch, with strong emphasis on observability, evaluation rigor, and measurable impact (80–90% reduction in manual data entry).”

“Built and scaled an AI-powered voice/chat patient engagement platform at Penn Medicine from early prototype into production clinical workflows, focusing on latency, edge cases, and user trust. Strong in LLM reliability engineering (structured prompts, validation/fallbacks), real-time troubleshooting with observability, and cross-functional enablement through pilots, demos, and sales/customer partnership.”

“Built and deployed a production LLM-powered phone assistant for a healthcare clinic, combining streaming STT/TTS with RAG over approved clinic documents and strict safety guardrails to prevent unverified medical advice, plus seamless human handoff. Also has hands-on Apache Airflow experience building robust daily ML/data pipelines with data validation, retries/timeouts, monitoring, and metric-gated model deployment, and iterates closely with clinic staff using real call reviews.”

“Built and deployed Clyra.AI, an AI-driven daily scheduling product that uses a LangGraph-based multi-agent LLM pipeline (task extraction, verification, reflection) grounded with strict RAG over emails/documents/calendars and real-world signals like health metrics. Designed a custom agent orchestrator with bounded loops/termination conditions and a self-auditing verification/reflection layer to reduce hallucinations while controlling latency and cost via caching and model distillation.”

“Built and shipped Serrano AI, a multi-tenant SaaS conversational AI platform that automates Odoo ERP workflows and lets ops/finance/supply-chain teams query ERP data in natural language. Implemented a multi-agent architecture (LangChain/LangGraph/CrewAI) with hybrid RAG over ERP schemas, deployed on Heroku/Vercel with production observability, cutting reporting time by ~80% while addressing hallucinations, latency, and schema complexity.”

“Unity VR developer who has shipped on Meta Quest, including Metro Awakening (Steam Awards 2024 VR Game of the Year) as an AI Programmer, focusing on performance-critical multi-agent AI optimization (EQS/HTN) for Quest 2. Also shipped Final Fury, taking ownership across gameplay, UI, networking (sync mechanics), and AI on a small team, and built a data-driven gesture/move system for VR fighting prototypes.”