AI Platform Engineer with 7+ years across cloud infrastructure, agentic AI systems, and cost optimization. I sit at the intersection of platform engineering and applied AI, building the infrastructure that runs LLM workloads and the product-facing tooling on top of it.
Currently at Trading Technologies (following OpenGamma's acquisition), where I lead FinOps and cost governance across a large-scale AWS organization and drive AI adoption across engineering. I'm currently running a joint PoC with AWS on Amazon Bedrock AgentCore for a multi-tenant AI assistant, and leading the org's migration from Datadog to Grafana.
I design and ship AI-native tooling end to end: MCP servers integrated with AWS Bedrock, autonomous agent pipelines that run cost analysis and operational intelligence unattended, and AI features that surface insights directly to internal users and customers. I've defined the org-wide pattern for how LLMs get integrated into our products, and authored the cost-governance guardrails framework now used as the baseline for every new AWS account.
Platform & AI: AWS architecture, Infrastructure as Code (Terraform, Terragrunt, Pulumi), CI/CD, and a deep, hands-on AI stack: Amazon Bedrock (Claude), the Model Context Protocol, retrieval and tool-use agents, and self-hosted open-weight models on GPU infrastructure.
Product: I take AI integrations from prototype to production — chatbots and analytics assistants for customer-facing portfolio and cost data, plus full-stack side projects (Next.js, Cloudflare Workers) where I own the whole loop from infra to UI.
Outside of work I run a homelab of autonomous AI agents and self-hosted LLMs, and I'm continually shipping side projects to push what AI-assisted engineering can do. Passionate about using AI to multiply engineering output, for the team and the product.