Professional Overview
I design and build production-grade AI systems that replace manual work, accelerate product timelines, and scale reliably under real-world load. Over the past 6+ years, I’ve led engineering across startups and production platforms - delivering AI-driven automation, full-stack SaaS products, and high-performance backend systems used by growing teams
Experience
AI Expertise
Skills
Employment Type
Description of Responsibilities
- Led AI integration for Guestbook platform systems
- Built scalable Node.js/TS pipelines for user data
- Designed async queues/workers for load handling
- Automated data flows between platform and CRMs
- Contributed to full-stack Next.js/API development
Key Achievements / KPIs
- Cut manual moderation effort by 40-60%
- Improved system performance under growing load
- Reduced PostgreSQL latency and boosted consistency
- Eliminated repetitive ops via CRM automation
AI Expertise
Skills
Employment Type
Description of Responsibilities
- Led end-to-end development of 4 startup MVPs
- Improved architecture on 3 additional MVPs
- Defined product scope with founders directly
- Built AI automation and data pipelines for leads
- Delivered secure multi-tenant SaaS with auth
Key Achievements / KPIs
- Reduced delivery timelines by 30-40%
- Cut manual workflows by 40-70% via AI
- Reduced backend/db latency by up to 35%
- Accelerated deployments by ~40% via CI/CD
AI Expertise
Skills
Employment Type
Description of Responsibilities
- Built medical record review systems for insurance
- Developed scripts to structure unstructured records
- Applied OCR and NLP for medical data extraction
- Created internal tools for case tracking efficiency
- Assisted backend services and AWS deployments
Key Achievements / KPIs
- Cut manual effort by 30-40% via automation
- Improved data extraction accuracy with NLP/OCR
- Enhanced reviewer efficiency with internal tools
- Maintained data security in AWS environments
Education
Field of Study: Computer Science
Areas of Expertise
Automation & AI Workflows
Build intelligent automation pipelines, integrate AI APIs into existing tools, and replace manual workflows with agentic AI systems.
AI & Machine Learning Engineers
Design, train, and ship production ML models — from data pipelines to model inference at scale. Covers supervised learning, neural networks, LLM integration, and model optimisation.
NLP & Prompt Engineering
Build natural language processing systems, fine-tune large language models, and craft reliable production prompts for AI-powered products.
