AI Engineering Lead — Autonomous Lab AI Platform

Substrate Bio Ltd; Greater London; Hybrid; GBP 120,000 - 180,000; Full time

Benefits offered by this job

30 days annual leave

Learning budget

Job summary

Substrate is building an autonomous wet-lab platform with AI-enabled intelligence software. The AI Engineering Lead will be the first engineering hire on the intelligence product, writing production code, shaping architecture, and guiding the growing team.

You will work closely with the founders, align two products (AI Scientist and AI Assays) to operational data, and drive the harness layer, data pipelines, and deployment culture as the platform scales.

Qualifications

• Five or more years of professional software engineering experience.
• Direct experience putting LLMs, foundation models, or agentic systems into production at scale.
• Working with the LLM harness layer: token economics, retrieval, evaluation, structured output, and large-scale data processing.
• Strong working knowledge of Python.
• Track record of designing systems that other engineers build on top of.
• Nice to have: biology/ biotech experience.
• Nice to have: early-stage founding-engineer role at a venture-backed company.
• Nice to have: knowledge of LIMS, ELN, or scientific data infrastructure.

Responsibilities

• Lock the architecture for AI Scientist and the harness layer.
• Ship the end-to-end literature ingestion, gap identification, and agentic loop.
• Define data capture infrastructure and the feedback path from operational software.
• Coordinate the intelligence team's work across product surfaces.
• Move from coding to coordinating the team’s efforts across projects.

Skills

LLM production

Foundation models

Agentic systems

Python

System design

Job description

Substrate is building an autonomous wet-lab platform with AI-enabled intelligence software. The AI Engineering Lead will be the first engineering hire on the intelligence product, writing production code, shaping architecture, and guiding the growing team.

You will work closely with the founders, align two products (AI Scientist and AI Assays) to operational data, and drive the harness layer, data pipelines, and deployment culture as the platform scales.