---
title: 'Senior AI Engineer at Causaly'
canonical: 'https://feeny.ai/job/senior-ai-engineer-causaly-london-mztv82p0bjxp'
type: 'job'
last_seen: '2026-09-06'
---

# Senior AI Engineer at Causaly

- **Company:** Causaly
- **Location:** London, United Kingdom
- **Employment:** full-time
- **Work type:** hybrid
- **Posted:** 2026-03-04
- **Last confirmed live:** 2026-09-06
- **Apply:** https://jobs.ashbyhq.com/causaly/0d240789-10ba-4a84-89fc-76f7e62079c0/application

**Skills:** Python, PyTorch, TensorFlow, LangChain, LLMs, NLP, API Development, CI/CD, Containerization, Version Control, Unit Testing, Integration Testing, Model Evaluation, Prompt Engineering, Fine-tuning, MLOps, LLMOps

> Design and implement end-to-end ML/AI solutions for biomedical knowledge platforms, focusing on generative AI and agent-based systems. The role involves applying strong software engineering principles, evaluating LLM and NLP techniques, and mentoring junior engineers to deliver reliable, production-ready AI features.

## Job description

About us:

Causaly is redefining how humans acquire knowledge and develop insights in biomedicine. Our AI-powered platform enables researchers and decision-makers to discover and interpret evidence from millions of scientific publications, clinical trials, regulatory documents, and other complex data sources in minutes.

We are building the world’s most advanced biomedical knowledge platform, powered by a high-precision Knowledge Graph and GenAI capabilities. Our technology is already used by leading biopharmaceutical organizations to accelerate drug discovery, improve safety, and drive better decision-making.

Backed by top-tier investors including ICONIQ, Index Ventures, Pentech, and Marathon, we are scaling rapidly and expanding our product suite and market presence.

## ABOUT THE TEAM

We’re hiring AI engineers to help us transform research outcomes in biomedical sciences. We utilise generative AI and agents to help scientists find novel connections and insights from biomedical literature and datasets.

Delivering a faster research experience is not just a matter of picking the latest LLM model. Getting accurate, scientifically relevant, trustworthy and meaningful results relies on building trust with our users that comes from integrating proper levels of guardrails, biomedical curation, consistent update cycles and robust deployment practices that make our platform a one-stop shop for a researcher’s needs.

We’re looking for AI engineers who will champion this cause and help us apply AI to transform the way biomedical professionals carry out their research and day-to-day exploration.

## WHAT YOU’LL BE DOING

- Design and implement ML/AI solutions end-to-end, from the idea and data exploration phase to deployment and monitoring, balancing cutting-edge techniques with pragmatism to deliver measurable impact.
- Apply strong software engineering principles, such as modularity, testing, code reviews, CI/CD and observability, to ensure AI systems are reliable, maintainable, production-ready and can be readily adapted to future developments.
- Choose the right approach for the problem at hand, evaluating classical ML and NLP techniques, LLM-based solutions, and agentic solutions to balance trade-offs between speed, cost, complexity, interpretability, and performance.
- Collaborate closely with product, design, and other engineering teams to scope work, align on success metrics, and incrementally ship improvements in user-facing features powered by AI.
- Document system architectures and decision rationale early and clearly, enabling alignment across teams and accelerating onboarding and iteration.
- Champion model and data quality, including dataset versioning, robust evaluation, fairness/bias assessment, and real-world performance tracking.
- Mentor junior AI engineers and cross-functional teammates, sharing best practices in modelling, coding, maintaining and integrating product features, and helping grow a high-trust, high-performance team culture.
- Stay up-to-date with emerging research and tools, distilling key insights and bringing back relevant innovations to elevate team capabilities and product opportunities.
- Contribute to a culture of knowledge sharing, through company-wide Slack channels, Show and Tell presentations and technical deep-dives.

## WHAT EXPERIENCE YOU’LL NEED TO BE SUCCESSFUL

- A master's degree or above in Computer Science, Electrical Engineering or a related field.
- 5+ years of experience building AI/ML systems in production environments, including ownership of key lifecycle stages: data collection, modeling, evaluation, deployment, and monitoring.
- Proficiency in Python and modern ML and agentic frameworks such as PyTorch, TensorFlow, or LangChain, with experience packaging models into APIs or integrating them into applications.
- A solid understanding of LLMs for natural language processing applications, including topics such as embeddings, prompt engineering and fine-tuning.
- Strong software engineering foundations such as version control, unit/integration testing, CI/CD, containerization plus a mindset of building for reliability and scale.
- Experience working in product-focused teams, collaborating with designers, engineers, and PMs, to scope and ship AI features iteratively
- Ability to reason about system behavior end-to-end, including model performance, latency, and observability, and how these impact user experience.
- Clear, structured communicator, comfortable documenting and defending architectural decisions and engaging in thoughtful technical debate.

NOT REQUIRED, BUT IT’S A PLUS IF YOU ALSO HAVE:

- Experience with MLOps/LLMOps frameworks and best practices
- A PhD in Computer Science, Electrical Engineering or a related field.
- A background or work experience in life-sciences, health-tech, or other data-intensive domains

## BENEFITS

💰 Competitive compensation package

🩺 Private medical & dental insurance

📔 Life insurance (4 x salary)

🤓 Personal development budget

🧘 Individual wellbeing budget

🌴 25 days holiday plus bank holidays

🥳 Your birthday off!

🚀 Potential to have real impact and accelerated career growth as a member of an international team that's building a transformative AI product.

We are on a mission to accelerate scientific breakthroughs for ALL humankind, and we are proud to be an equal opportunity employer. We welcome applications from all backgrounds and fairly consider qualified candidates without regard to race, ethnic or national origin, gender, gender identity or expression, sexual orientation, disability, neurodiversity, genetics, age, religion or belief, marital/civil partnership status, domestic / family status, veteran status or any other difference.

## About Causaly

## Company Overview
- **One-liner**: Causaly is an agentic AI platform for life sciences R&D that accelerates discovery and development with scientific rigor.
- **Entity Type**: Private (Series B funded)
- **Headquarters**: London, United Kingdom (offices also in New York and Greece)
- **Founded**: 2018
- **Founders**: Yiannis Kiachopoulos (CEO) and Artur Saudabayev (CTO)

## Core Business
- **Primary industry/industries**: Life sciences AI, drug discovery and development, biomedical research
- **Target customers**: B2B – pharmaceutical and biotech enterprises (R&D teams, scientists, regulatory affairs)
- **Mission or purpose statement**: “To accelerate discovery in life sciences through transformative AI technologies” [causaly.com](https://www.causaly.com/about)

## Products & Services
- **Causaly AI Platform**: A purpose-built agentic AI workspace for scientific decision-making. It combines a high-precision Scientific Knowledge Graph (500M+ facts, 70M+ directional relationships) with a Commercial Knowledge Graph for drug landscape intelligence. Features include:
  - **Scientific Information Retrieval System (SIRS)**: Rigorous, hallucination-filtered search with cited evidence.
  - **Enterprise Data Fabric**: Ingests 100k+ documents per day and integrates client data, APIs, and agentic frameworks.
  - **Agentic Orchestration**: Domain-specialized AI agents collaborate, cross-validate, and automate workflows (e.g., target identification, indication discovery, portfolio intelligence, evidence validation for regulatory filings). [causaly.com](https://www.causaly.com/)

## Market Standing
- **Valuation/Market Cap**: Not publicly disclosed
- **Key Metric**: Annual revenue of **$32.8M** (estimated, as of 2025) and **$93M in total funding** (4 rounds) [uk.linkedin.com](https://uk.linkedin.com/company/causaly)
- **Notable Investors/Partners**: 
  - **Lead investors**: ICONIQ Growth (Series B, $60M), Index Ventures (Series A), Pentech Ventures, Marathon Venture Capital [cbinsights.com](https://www.cbinsights.com/company/causaly)
  - **Strategic advisors**: David M. Lee (former Chairman & CEO of Johnson & Johnson), Marcus Schindler (former CSO of Novo Nordisk) [causaly.com](https://www.causaly.com/about)
- **Growth Signals**: 
  - 113 employees (+1.6% YoY) [uk.linkedin.com](https://uk.linkedin.com/company/causaly)
  - Active job postings up **400% year-over-year** [uk.linkedin.com](https://uk.linkedin.com/company/causaly)
  - Operating in 10 countries (including US, Greece, Spain, Sweden, Japan)
  - Supports 100+ programmes from discovery to early clinical stages

## Competitive Advantages
- **Purpose-built for life sciences**: Not a generic chat AI; every layer is designed for scientific rigor, traceability, and factual grounding.
- **High-precision knowledge graph**: 500M+ facts and 70M+ causal relationships enable deep biological reasoning.
- **Agentic orchestration with quality control**: Domain-specialized agents collaborate, cross-validate, and hand off tasks, reducing hallucination risk.
- **Enterprise data fabric**: Integrates proprietary client data, MCPs, and APIs, creating a single source of truth that compounds over time.
- **Advisory network**: Deep ties to pharma leaders (ex-J&J, ex-Novo Nordisk) provide credibility and domain expertise.

## Strategic Focus
- **Current priorities**: Expanding into new markets (e.g., EMEA, US), deepening use cases across the full R&D pipeline (early research → clinical → post-market), and scaling enterprise adoption.
- **Direction**: Codify specialized workflows, automate critical scientific decisions, and become the “operating system” for biomedical data. [causaly.com](https://www.causaly.com/about)

## Why Work Here
- **Culture**: Mission-driven, collaborative, and fast-paced. Values include ownership, openness, and tackling hard problems. [causaly.com](https://www.causaly.com/about)
- **Remote/hybrid policy**: Not explicitly stated on careers page, but global presence (London, New York, Greece) suggests a hybrid or flexible model.
- **Team & leadership**: SVP of Engineering Morgan Bruce (ex-Maze, FNZ, Onfido) scaled engineering teams to 100+ people across five countries. VP People Liat Shtainberg (ex-Bumble, Trainline) brings scale-up expertise. [causaly.com](https://www.causaly.com/about)
- **Notable perks**: Opportunity to work on cutting-edge AI for life-saving treatments; strong emphasis on professional growth and impact.

## Sources
1. [causaly.com](https://www.causaly.com/)
2. [causaly.com/about](https://www.causaly.com/about)
3. [uk.linkedin.com/company/causaly](https://uk.linkedin.com/company/causaly)
4. [cbinsights.com/company/causaly](https://www.cbinsights.com/company/causaly)
5. [jobs.ashbyhq.com/causaly](https://jobs.ashbyhq.com/causaly)

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