Forward Deployed Engineer

Forward Deployed Engineer

Department: Engineering

Employment Type: Full Time

Location: UK

Location: UK (Remote)

Reports to: VP Technology

We’re hiring a Forward Deployed Engineer to work directly with customers as they integrate our knowledge graph into their own systems.

Our customers are typically data science and bioinformatics teams in pharmaceuticals or biotechs. You’ll work closely with customer technical teams to get our data products into production. That might mean loading the graph into Neo4j, exposing it through APIs, flattening it into analytical warehouses, or helping customers use it in LLM and agent workflows. Sometimes the customer team will own most of the implementation;

sometimes you’ll build large parts of it yourself.

In this highly impactful role; you’ll take technical ownership from trial through to a working deployment. The role is roughly 70% customer-facing delivery work and 30% contribution to our core platform.

Based in our Engineering team you’ll blend customer delivery with engineering in our core platform team; turning repeated customer problems into reusable product capabilities.

What We Do

Research and Development in the pharmaceutical industry is time-consuming, expensive, and often overlooks valuable data insights. We’re changing that with AI-powered data science solutions that uncover hidden insights to support more efficient and informed drug discovery. Using AI and Natural Language Processing (NLP), our technology extracts and structures data from millions of scientific documents, identifying causal biological relationships and organising them into knowledge graphs.

This advanced data science empowers bioinformaticians and biologists with a deeper understanding of the connections between diseases, proteins, and drugs.

Our team consists of biomedical and data science experts with real-world lab and pharmaceutical experience. These specialists ensure that our solutions are scientifically grounded, delivering accurate, reliable data to our customers.

The Company

Biorelate is a venture backed Series A startup (supported by established Tech investors). If you’re eager to collaborate with exceptional scientists, software engineers, and subject matter experts from various fields in a supportive, ego-free environment, Biorelate is the place for you.

Lead customer integrations

• You’ll lead customers through the full implementation lifecycle - supporting technical scoping during pre-sales with the Senior Solutions Consultant, through onboarding and production rollout.
• You’ll help define what’s feasible, estimate effort, identify risks early, and then own delivery once the engagement starts.

Design integrations for AI and agent workflows

• A growing number of customers want to use our graph inside agentic systems. You’ll help design and implement architectures around graph RAG, MCP, retrieval systems, and APIs for agentic use cases.

Contribute to technical scoping

• You’ll partner with the Senior Solutions Consultant during the requirements and proposal stages to validate technical feasibility and shape realistic implementation plans.
• The Senior Solutions Consultant owns qualification and the commercial process; you help determine what can actually be delivered and what it will take.

Drive productisation

• You’ll identify reusable components, recurring integration patterns, and capabilities that belong in the core product rather than custom delivery work.

Contribute to the platform

• Outside of customer delivery, you’ll work alongside the wider engineering team on the core data and ML platform.

We're looking for someone with strong experience building and deploying machine-learning-based data systems, who's ready to take that expertise into a high-impact customer-facing role. You should be comfortable working with the core building blocks of these systems rather than just on top of them.

A machine learning or data science background is valuable, you'll have first-hand experience of the problems our customers are wrestling with. Candidates who have combined experience across data engineering and data science would be ideal, but while we…