15+ years building real systems.

Designed, built, and deployed production AI/LLM systems and automation pipelines for enterprise-scale workflows.

• Led transition to a prose-first agentic AI operating model, deploying production AI agents across engineering, QA, and product workflows — improving productivity by 30% and eliminating up to 100% of select manual processes.
• Architected production-grade agentic AI systems and document intelligence platforms using LLM pipelines, retrieval workflows, and structured extraction, generating $250K+ in annual efficiency gains.
• Established architectural standards for reproducible AI environments and secure containerized microservices.
• Designed and trained supervised ML models for intelligent form classification, increasing automated field-mapping accuracy by 40%.
• Conducted executive-level build-vs-buy analysis (custom ML vs. AWS Comprehend) to guide long-term AI investment strategy.
• Designed and implemented AI-driven QA automation framework, increasing test coverage to 80% and reducing regression defects by 50%.
• Partnered with cross-functional leadership to align AI platform development with business outcomes, risk posture, and delivery timelines.

Founded and led an AI-driven automation consultancy focused on modernizing business workflows and deploying scalable AI systems.

• Designed and launched AI-powered SaaS platforms, including LLM-based career automation systems with subscription monetization and browser-automation integration.
• Architected secure cloud-native systems and AI integration pipelines.
• Delivered up to 60% operational efficiency improvements across client organizations.
• Directed product roadmap, integration strategy, and monetization architecture.
• Worked directly with clients to translate business problems into deployable AI agent solutions.
• Explored integration of conversational and multimodal AI systems for customer interaction workflows.