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Location: Austin, TX

Remote: Yes (5+ yrs fully remote)

Willing to relocate: Yes, for the right role

Open to: Full-time or contract

Technologies: Claude Agent SDK, MCP (author + consumer), RAG, evals, Langfuse, LLM-ops; AWS (EKS, Lambda, Bedrock) + Azure (AKS, ADO); Databricks, Terraform, Kubernetes; Python, TypeScript, Rust

Résumé: https://drive.google.com/file/d/13j_Ax_0soXWrtoMfFORqV4A34kn...

LinkedIn: linkedin.com/in/branperez

GitHub: github.com/BrandonPerez-Dev

Email: perez.brand.on.off at gmail dot com

I build AI agents and the platforms they run on. This year, on WEX's incubator team, I built a platform on the Claude Agent SDK: a runtime, an agent builder, a builder MCP, and skill-graph composition for sub-agents. It took new-agent build time from weeks to days, and I used it to build several agents. The customer-facing ones I demoed to WEX's C-suite.

Before that I built SSM Health's first internal agent platform. The "AI Agent Factory" took new-agent spin-up from weeks to hours. I stood up their first LLM observability stack, Langfuse on AWS EKS, and built the HIPAA-compliant cross-cloud ML infrastructure underneath it. I came up through cloud and platform engineering, so I build the infra myself.

I also wrote Ostia, an open-source Rust MCP server that sandboxes AI agent shell calls at the OS level with Landlock, seccomp, and Linux namespaces: github.com/BrandonPerez-Dev/ostia. Once it was solid, I started handing agents small CLIs as tools through that sandbox instead of standing up a separate MCP server per integration.


Location: Austin, TX

  Remote: Yes

  Willing to relocate: Yes

  Technologies: Vercel AI SDK, Graph RAG, Langgraph, Openai Agent SDK, Langfuse, Databricks, MLOps, DevOps, Typescript, Python, Java, Azure, AWS, cloud architecture, express, docker, k8s, datadog, react

  Résumé/CV: https://www.linkedin.com/in/branperez/

  Email: perez.brand.on.off@gmail.com


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