Most people calling themselves "AI consultants" are selling a slide deck and over-prescribed and hyped solution they read
about on a LinkedIn influencer's post. When it comes to building, they will ask their LLM for a SOW and vibe-code an
implementation ripe with bugs that will never scale or hold up under scrutiny or a security review.
I build actual systems.
Things like clinical AI running across 100k+ patient
encounters, the data platforms that support them, and the secure, scalable, and resilient infrastructure
that stays up when a vendor API starts throwing 500s in the middle of an expensive batch run.
I've also spent real time hardening vibe-coded prototypes that collapsed when production
data hit them. When a demo has to become something that survives regulators, real patients, and
scale, that's when people reach out to me.
— AI & agentic systems: Architecture tailored to fit the use case
— Traditional software & platforms: Sometimes you don't need AI in your implementation or product
— Data platform & pipeline engineering: Bigquery, Snowflake, Databrick, dbt, Airflow, Dataflow, etc etc.
— Healthcare / Clinical AI at scale: HL7 FHIR, LLM extraction, clinical decision support, automated workflows
— Secure & Scalable Cloud infrastructure: Google Cloud, AWS, Azure
— On premise / Colocated Solutions: Extensive physical systems design experience. I have built GPU servers.
— Hardening & productionizing: Production deployments have to survive a real load.
— Security: Security reviews & pre/post audit remediation for regulated industries (healthcare, government) at the code, infra, and even physical layers.
Based in Houston, Texas and serving Austin, San Antonio, Dallas, Greater Texas, and remote. Twenty years across
data, ML, software, and platform engineering, with co-authored AI research (arxiv, 2026). rm@engabe.com