20+ years engineering intelligence into the enterprise.
20+ years engineering intelligence into the enterprise. From early enterprise systems to autonomous decision platforms. The through-line is designing systems that reason, decide, and ship. AI workflow engineering, agentic architecture, and decision intelligence applied at Fortune 50 scale.
Built and shipped EdgeQuant.AI as a high-availability, multi-agent autonomous trading platform running in production. The work went far beyond prompt engineering and vibe coding. The real engineering was in API interactions, asynchronous execution paths, latency-sensitive inference, schema validation, idempotency, reconciliation, and graceful degradation when data or inference providers degrade.
The architecture uses multi-model failover and routing between Claude, ChatGPT, and Gemini, with automated accuracy tracking and evals so the system uses the right model for the right job and detects when a provider degrades. Cron jobs, web extraction through Firecrawl, Supabase persistence, and real-time market data feeds all operate under failure-aware contracts with retries, freshness checks, and silent-failure detection.
Every agent runs inside a typed, observable workflow with persistent state, telemetry, and self-healing retries. The platform is also the applied AI R&D lab and go-to-market vehicle for a portfolio of enterprise agent product concepts.
- Shipped a production high-availability multi-agent trading platform from zero to live deployment, designed for asynchronous execution, latency-sensitive inference, and real-time risk gating
- Built multi-model failover and routing across Claude, ChatGPT, and Gemini with automated accuracy tracking and evals
- Architected 14 enterprise AI agent product concepts and integrated them into a unified applied AI go-to-market portfolio
- Designed resilient agent workflows with persistent memory, self-healing retries, and telemetry that remove manual intervention and keep the system reliable under failure
- Engineered API orchestration, cron scheduling, web extraction, and database layers that handle provider failures, degraded payloads, and silent data loss without human intervention
- Applied AI engineering beyond prompt engineering: schema validation, idempotency, reconciliation, observability, and failure isolation as core product capabilities
Built and scaled the Digital Solutions and AI automation capability across LinkedIn Finance, from foundational process automation and analytics to machine learning, generative AI, and agentic workflows embedded in real Finance processes. Led transformation across Controllership and Quote-to-Cash, then expanded into Strategic Finance to shape AI strategy, roadmap, and use-case portfolio. Today, AI agents and intelligent workflows are integrated directly into Finance operational applications and executive decision-making, moving AI from experimentation into production business processes.
- AI Strategy, Vision & Roadmap: Shaping the AI and automation strategy, vision, roadmap, and use-case portfolio across Finance, connecting business priorities with AI, agentic automation, data, and process transformation.
- Digital Solutions & AI Adoption: Built and scaled Digital Solutions capabilities from traditional automation and analytics into GenAI and agentic workflows, embedding AI into real Finance processes rather than isolated experimentation.
- Strategic Finance Expansion: Expanded AI and automation leadership into Strategic Finance, defining the vision and roadmap, identifying and prioritizing use cases, and translating high-value opportunities into executable AI and automation solutions.
- Enterprise AI & Agentic Workflows: Driving practical adoption of Claude, ChatGPT, Gemini, Microsoft Copilot, prompt systems, evaluations, guardrails, and agentic workflows across Finance use cases.
Cloud-native thinking, SaaS economics, and automation at carrier scale, well before AI was the word for it.
- Accelerated WebEx from machine-based infrastructure to cloud. 40% more scalable, 30% lower operating cost, 10,000+ users
- Supported $15M in customer opportunities through automation-driven adoption strategies
- 25% improvement in implementation effectiveness and time-to-value across cross-functional deployments
Where the operator's instinct was formed: find the friction, measure it honestly, automate it well.
- Automated finance processes across enterprise systems. 300+ manual hours removed monthly, 30% efficiency gain
- 20% process performance lift by translating operational pain points into scalable, cross-functional solutions