
tech workers
@techworkers
I build production AI systems, LLM automations, and scalable machine learning pipelines.
What I'm looking for
I've built production AI systems and automation workflows at Waabi, Vention, and Spellbook, connecting LLMs, cloud platforms, and business systems to solve operational problems.
At Waabi, I develop n8n, Zapier, and Python workflows for document classification, BOM data extraction, customer queries, data transformation, web scraping, and SaaS integrations.
At Vention, I built and deployed machine learning models and low-latency Python microservices using PyTorch, TensorFlow, Scikit-Learn, REST APIs, GCP Vertex AI, and AWS. I also implemented model monitoring, drift detection, testing, logging, and reproducible ML experimentation with MLflow and Git.
At Spellbook, I designed agentic workflows and autonomous assistants using OpenAI, Anthropic, n8n, and Python microservices. I focus on reliable production automation through secure APIs, monitoring, retry logic, and scalable integrations.
Experience
Work history, roles, and key accomplishments
Developed automated integration workflows using n8n, Zapier, and Python scripts to connect cloud-based design platforms with internal business systems. Supported LLM API integration for document classification, BOM data extraction, and customer query responses.
Built, trained, and evaluated machine learning models using PyTorch, TensorFlow, and Scikit-Learn. Designed and maintained end-to-end ML pipelines for data ingestion, feature engineering, model training, and continuous deployment on cloud platforms.
AI Automation Engineer
Spellbook
Jun 2020 - Jan 2022 (1 year 7 months)
Architected and deployed agentic workflows using n8n and custom Python microservices to automate telemetry data pipelines and operational processes. Integrated OpenAI, Anthropic, and custom LLM APIs to build autonomous assistants for anomaly detection and report generation.
Education
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tech hasn't added their education
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