Solutions Engineer

Our New York based client is building autonomous agents that do data engineering. Not a chatbot that suggests SQL - agents that read your source systems, design the bronze-to-gold mappings, write and test the dbt models, commit them to Git with a PR, then watch the pipeline run and fix themselves when it breaks.

Both founders were early employees d stage, six engineers, and enterprise customers already running it across financial services, healthcare and media.

They want another 2 Forward Deployed Engineers.

You'd be the one going into a bank's data environment and making it work - configuring the platform, designing the blueprints, wiring it into whatever already exists, debugging live in the room across Docker, AWS, Snowflake and Python. Then taking what you learn back to the engineers building the thing.

Here's the honest bit: nobody hands their data infrastructure to an autonomous agent unless they trust the person who set it up. That's the actual job.

The non-negotiables, so nobody wastes an afternoon:

• New York. Hybrid, onsite with clients when it counts.
• No sponsorship or visa transfer. You need to be authorised already.
• 5+ years technical and client-facing in data - FDE, Solutions Engineer, or consulting delivery. Post-sales deployment you owned, not pre-sales demos. 6+ is where they're really looking.
• You've owned dbt. Not "used Snowflake somewhere that had dbt" - built and shipped the models yourself.
• LLM or agent-based systems you've put into production.
• Cursor or Claude Code, daily.
• Python at configuration level, plus Docker, CI/CD and orchestration.

And before anyone asks about that last one - no, you don't need to be a hardcore Python engineer. You need to be able to read it, change it and not panic.

If you've spent the last few years deploying data platforms inside enterprise clients - Accenture, Deloitte, Slalom, Snowflake, Databricks, that world - this is the rare start-up role that specifically wants that background rather than screening it out.