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Forward deployed engineer - biotech ai start-up

Leicester
Harnham Search & Selection
Engineer
Posted: 22 May
Offer description

Do you want to work on production AI systems used by global pharmaceutical companies?

Have you built LLM or data platforms that needed to work reliably in real customer environments?

Are you ready to operate at the intersection of AI Engineering, platform architecture, and enterprise delivery?


A Series A biotech AI startup is hiring a Forward Deployed Engineer to help enterprise customers integrate cutting-edge AI and knowledge graph technology into production workflows. Their platform combines NLP, LLMs, retrieval systems, and biomedical knowledge graphs to uncover relationships between diseases, proteins, and drugs across millions of scientific documents.


The business works with pharmaceutical and biotech organisations globally and is scaling customer onboarding significantly following strong commercial traction. You’ll join a highly technical, remote-first team focused on solving complex scientific and engineering problems with real-world healthcare impact.


This role sits between AI Engineering, Solutions Engineering, and customer delivery. You’ll work directly with technical customer teams to scope, architect, and deploy production AI workflows while also contributing to the company’s core platform and reusable capabilities.


Key Responsibilities

• Lead customer AI/data integrations from discovery through deployment

• Design and implement RAG, retrieval, and agentic AI workflows

• Build integrations around APIs, orchestration systems, and data pipelines

• Support deployment of LLM-powered systems into production environments

• Contribute to reusable platform capabilities and internal tooling

• Work closely with enterprise stakeholders and customer engineering teams

• Help architect solutions involving knowledge graphs, vector search, and cloud infrastructure


Key Details

• Salary: £80k–£130k + equity/share options

• Working model: Fully remote (UK-based) with occasional travel

• Stack: Python, LLMs, RAG, Neo4j, vector databases, Spark, dbt, Airflow/Dagster/Prefect, cloud warehouses

• Sponsorship: Currently unavailable


Interested? Please apply below.

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