Founding Applied AI Engineer

This is a founding applied-AI role. You'll be building our core data pipeline and intelligence layer with the founding team from 0 to 1 You'll be tackling our largest technical challenges across technologies.

Responsibilities:

• Design and build data pipelines that capture and turn high volumes of system activity into structured, queryable data.
• Turn raw activity streams into processes: sessionise event logs, cluster recurring sequences, and use LLMs to label and summarise what's happening.
• Build the evaluation backbone from scratch: stand up synthetic data generation pipelines that produce labelled scenarios to measure accuracy and catch regressions.
• Own data quality and privacy.
• Partner closely with the founders and the rest of engineering to ship features end to end.

Requirements:

• 1-4 years of experience in data engineering, AI/ML engineering, or backend work with a data focus (some of this can be project or research experience).
• Strong in Python and/or TypeScript, comfortable in SQL, and able to build data pipelines you can trust.
• Hands-on experience working with LLMs' structured output, prompting, and wrangling non-determinism while keeping behaviour reliable.
• A practical sense for evaluation: you know that "it looks right" isn't the same as "it's measurably right".
• Care about data privacy and handling sensitive information responsibly.
• Comfort with ambiguity and a real appetite to own a hard, open-ended problem.

Nice to Have:

• Background in process mining, sequence / event-log analysis, or workflow analytics.
• Deeper PostgreSQL: window functions, partitioning, pg_cron, query performance.
• Embeddings and vector search (pgvector) or semantic retrieval.
• Familiarity with cloud infrastructure.
• Any prior early-stage startup experience.
• Degree in computer science or a related field.