Bring in someone who builds both the data and the AI.
Most teams hit the same wall: the AI demo works, but the data underneath it does not hold up in production. I help with both ends of that problem, from the lakehouse and the pipelines to the RAG and ML systems that run on them.
Both ends of the same problem
Data engineering and AI engineering, weighted equally, because in production they are the same job.
Data Platform Engineering
Lakehouses, warehouses, and pipelines that are reliable, governed, and cheap to run.
- Medallion lakehouses on Azure, Databricks, and Delta Lake
- Snowflake ELT with Snowpark, Streams, and Tasks
- Event-driven and streaming pipelines on AWS
- Cost and cluster optimization on existing platforms
AI & LLM Engineering
RAG, ML, and LLM systems built on data foundations you can actually trust.
- RAG pipelines and LLM apps with vector search
- Recommendation, forecasting, and classification models
- Decision-support tooling, including healthcare use cases
- Prototype to production, with the data plumbing to match
Data Quality & Governance
The guardrails that keep a platform trustworthy as it grows.
- Great Expectations quality gates in the pipeline
- Schema-drift detection and alerting
- Lineage, audit logging, and access control
Architecture & Advisory
A second set of eyes before you commit to a direction or a bill.
- Architecture reviews for data and AI systems
- Cloud platform and tooling decisions
- CI/CD and reliability for data teams
Clear from the first call
No surprises on scope, timeline, or price. You always know what you are getting and when.
Scope
A short call to understand the problem, the constraints, and what done looks like. No charge, no pitch deck.
Plan
A clear proposal: the approach, the architecture, the timeline, and the price. You know exactly what you are getting.
Build
I ship in production, in the open, with regular check-ins. Config-driven and documented, so your team can own it after.
Handover
Working systems, clear docs, and a walkthrough. The goal is to leave you independent, not dependent on me.
Pick the shape that fits
From a single defined build to ongoing senior capacity on your roadmap.
Project build
A defined platform, pipeline, or AI system, scoped and delivered end to end.
Embedded support
Part-time senior capacity on your data or AI roadmap, for a set number of weeks.
Advisory and audit
Architecture review, a cost or reliability audit, and a prioritized plan you can act on.
Let's build something that ships.
Hiring for a senior Data/AI role, or need a data platform that actually holds up in production? Let's talk.
or email me directly at muhammaduzairkhan329@gmail.com