Collaboration
I join engineering teams as an embedded senior engineer — in their pull requests, Slack and architecture reviews — to design, build and automate data, cloud and AI systems.
What teams usually bring me in for, by area:
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Applied AI & MLOps. Taking an agent or RAG prototype to production with evaluation, telemetry and cost limits, and automating ML deployment.
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Cloud & Platform Engineering. Landing zones, zero-trust CI/CD and policy checks defined as code (Terraform / OpenTofu, GitHub Actions, OPA Rego), plus cloud cost reviews (FinOps).
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Data Engineering & Pipelines. Building or stabilizing batch and streaming pipelines (Spark, dbt, Airflow, Dagster), with tests, backfills and recovery.
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Data & Storage Architecture. Dimensional models, data contracts and the choice between a data warehouse and an open-table lakehouse.
Recent client work spans Banking and finance, Retail, and Energy — operating under strict regulatory, security, and data isolation constraints.
Working arrangements
Engagements. I work as an independent contractor, on a project basis: from a short architecture audit or design review (2–4 weeks) to several months as an embedded technical lead or senior engineer (3–6+ months), including code review and mentoring.
Clouds. My deepest experience is on Google Cloud; I also design and deploy on AWS regularly.
Time zones. I work from Caracas (UTC-4, no daylight saving), Monday to Friday from 08:00 to 20:00; the indicator under my photo on the home page shows whether I am in those hours right now. That covers the business day across the Americas and European afternoons. For an earlier European slot or a late US West Coast one, I can schedule a call between 05:00 and 22:00.