Forward Deployed Scientist

Perceptic; Greater London; Hybrid; GBP 90,000 - 130,000; Full time

Benefits offered by this job

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Job summary

Perceptic is seeking a Forward Deployed Scientist to work directly with customers—research scientists, clinical teams, and pharma decision-makers—to tailor the platform to their data and workflows. You'll map decision processes, design evidence models, build plug-ins to internal data sources, and refine prompts for reasoning workflows, then bring insights back to product.

This role sits inside the product team, with real ownership from week one and a path to influence how the platform supports

Qualifications

• Direct experience working with customers or users on hard technical problems.
• Comfort with code; you write Python, work with APIs, build plug-ins and design data models.
• Ability to explain gaps between what is asked for and what is needed.
• Strong communication across scientists and engineers.
• Comfort in ambiguity; bias to ship.

Responsibilities

• Embed with customers to understand their domain, workflows and decisions.
• Define how Perceptic should be configured for each customer: the evidence model, data sources, reasoning workflows, and success measures.
• Build plug‑ins to internal data sources, implement data models, prompt engineering, configurations and integrations.
• Drive adoption so users achieve better-grounded decisions, not just login.
• Take field learnings into product and engineering conversations to shape the next features.

Skills

Customer-facing experience

Python

APIs

Data modeling

Communication

Tools

Plug-ins

LLM tooling

Prompt engineering

Retrieval systems

Job description

Perceptic is the AI operating system for drug development. We connect evidence, data, decisions, and workflows across the lifecycle, so every insight compounds instead of getting lost across handoffs. Forward Deployed Scientists are how that reaches the people making the calls.

The role

You'll work directly with our customers: research scientists, clinical teams, and pharma decision-makers. The job is to understand how they reason, what evidence they trust, and where Perceptic can change the decisions they make. You own the work of turning the platform into something that fits a given organization properly, meaning their data, their workflows, their judgment.

A day might involve sitting with a clinical team to map how a go/no-go decision really gets made, reading up on their domain, designing the evidence model behind their workspace, building a plug‑in to an internal data source, or refining the prompts behind a reasoning workflow. Then pulling what you've learned back into the product by the end of the week.|

You'll sit deep inside the product team. What you see in the field becomes the next generation of the platform.

Office Location: Regent St, London (Hybrid, 2-3 days onsite)

Salary: Competitive + Options

What you'll do

• Embed with customers until you understand their domain, workflows and decisions well enough that they start telling you what's actually broken
• Define how Perceptic should be configured and extended for each customer: the evidence model, the data sources, the reasoning workflows, and the measure of success
• Build what's needed to make it real, including plug‑ins to internal data sources, evidence and data model implementations, prompt engineering, configurations and integrations
• Drive adoption, so that people are reaching better‑grounded decisions rather than just logging in
• Take what you see in the field straight into product and engineering conversations, and shape what we build next

What we value

• Direct experience working with customers or users on hard technical problems. That might be solutions engineering, applied science, forward deployed work, technical product, scientific consulting or something adjacent. Depth matters more than years.
• Comfort with code, motivated by the outcome. You write Python, work with APIs, build plug‑ins and design data models because you want the user on the other end to succeed.
• A sharp sense for the gap between what someone asks for and what they actually need, and the ability to explain that gap clearly to both sides.
• Strong communication across the full range, from a scientist explaining an assay to an engineer reviewing your data model.
• Comfort in ambiguity. Pharma data is rarely clean and requirements are rarely complete. You find the path through.
• Bias to ship. Rough in a user's hands this week beats polished next month.

Nice to have

• Background or working experience in pharma, biotech or life sciences, whether that's discovery, translational, clinical, regulatory, evidence generation or adjacent
• Hands‑on with LLM tooling, prompt engineering, agent frameworks or retrieval systems
• Early‑stage startup experience

The team you'd be joining

Perceptic was built by operators who have deployed AI where it matters. Our team has spent years building and running production AI systems inside some of the world's most complex and sensitive enterprise environments, including Palantir, and years inside the lab publishing the science. We have seen where AI succeeds, where it breaks, and what it takes for a serious organization to trust it. We're now applying that to drug development.

You'd be working alongside the founders and a small product team, with real ownership from the first week and no layers between you and the decisions that matter.

We're looking for the best in the industry

Drug development does not reward good enough, and neither do we. We are hiring a small number of people, and each one changes what this company is capable of, so the bar is high and deliberately so.

We want the people others in the field already call when the problem is hard: the scientist brought in when the data is a mess and the answer still has to hold up, the engineer who ships the thing everyone else scoped at a quarter, the person who can sit in a room with a Chief Medical Officer in the morning and a data model in the afternoon and be credible in both.

If that's the work you're already known for, and you want it pointed at decisions worth years of effort, billions in capital, and real patient outcomes, we'd like to talk.

Why Perceptic

Drug development is one of humanity's highest‑stakes forms of reasoning, and the systems supporting it were not built for the complexity of modern science. The future is not one model producing one answer. It is teams of scientists working with intelligent systems that remember, connect, challenge, and explain.

In this role you'll have an unusually direct impact on two things at once: whether a specific team at a specific company makes better decisions this quarter, and what Perceptic becomes over the next two years.

If you want to be close to the science and close to the build, this is the role to do it.