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Vetted AI Engineers in the Bay Area
Pre-screened and vetted in the Bay Area.
Senior Software Engineer specializing in Python AI/ML integration and experimentation pipelines
Junior Software Engineer specializing in AI infrastructure and applied machine learning
Chandra sai kiran Kammari
Mid-level Machine Learning Engineer specializing in fraud detection and real-time personalization
“ML/LLM engineer with Stripe and Adobe experience who productionized a transformer-based Payments Foundation Model for real-time fraud detection at global scale (billions of transactions). Built petabyte-scale ETL/feature pipelines (Spark/EMR, Airflow, dbt, Kafka/Flink) and achieved <100ms multi-region inference (EKS, TorchServe, edge/Lambda, GPU/CPU routing) with strong PCI-DSS/GDPR compliance and explainability (SHAP/LIME), reporting a 64% fraud accuracy improvement.”
Mid-level AI/ML Engineer specializing in LLMs, RAG pipelines, and MLOps
Mid-level AI/ML Engineer specializing in LLM RAG pipelines and cloud MLOps
Param Yanamandra
Staff/Lead Software Architect specializing in Contact Center platforms and GenAI automation
“Built and deployed production LLM systems in healthcare and at LinkedIn: automated pen-and-paper clinical trial evaluations with a 40x efficiency gain and created an evidence-based Evaluation Agent focused on accuracy and speed. Also used Temporal to orchestrate resilient data-ingestion workflows for customer support staffing prediction, improving prediction outcomes by 40% while handling missing data, retries, and backfills.”
Mid-level Machine Learning Engineer specializing in LLMs, RAG, and MLOps
Principal Salesforce Architect specializing in AI, AWS, and enterprise integrations
Leela Tikkisetty
Mid-level Software Engineer specializing in ML platforms and cloud-native backend systems
“Software engineer with experience at Google and the City and County of San Francisco building production AI systems, including a RAG-based internal support chatbot and ML-driven ticket priority tagging. Has scaled data/ML platforms with Airflow on GCP (1M+ records/day, 99.9% SLA) and deployed multi-component systems with Docker and Kubernetes (GKE), using modern LLM tooling (LangChain/CrewAI, Claude/OpenAI, Pinecone/ChromaDB, Bedrock/Ollama).”
Mid-level AI and Full-Stack Engineer specializing in LLMs and scalable web systems
Mid-level Machine Learning Engineer specializing in Generative AI and LLM applications
Aashna Kunkolienker
Junior AI Engineer specializing in agentic workflows and ML platforms
“Building a production LLM/agent system for a leading US dental provider that extracts rules from payer handbooks/portals and EDI 271 responses to validate and improve patient cost estimates. Combines GCP stack (BigQuery, GKE, Cloud Run, Pub/Sub, Vertex AI) with strong agent reliability practices (observability, validator agents, grounding, PII/hallucination guardrails, confidence scoring) and has led non-technical customer stakeholders on enterprise ServiceNow↔Aha sync and AI-powered enterprise search/summarization.”
Wei-Hsien Wang
Entry-level AI Engineer specializing in full-stack generative AI systems
“AI/full-stack product engineer who has shipped both user-facing and internal LLM products, from a photo-to-music recommendation app to an experimentation agent at Azazie. Stands out for combining modern app development with production-grade agent and GraphRAG systems, including a 500k+ email analysis platform and measurable impact like 3x experiment velocity, 75% setup-time reduction, and 65% faster task discovery.”
Junior AI Engineer specializing in GenAI, RAG, and agentic systems
Mid-level Full-Stack Software Engineer specializing in AI-powered web applications
Mid-level AI/ML Engineer specializing in LLM pipelines, RAG systems, and agentic automation
Entry AI Application Engineer specializing in GPU infrastructure benchmarking
Mid-level AI Engineer specializing in agentic workflows and RAG systems
Senior Software Engineer specializing in backend systems and LLM-powered products