Strong fit for experienced engineering leaders who shape AI-first workflows and prioritize customer outcomes, with a background in distributed teams and biomedical tech.
Derived from job-description analysis by Serendipath's career intelligence engine.
Original posting from Causaly via Ashby
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.
Leading the engineering organisation responsible for our agentic research product and customer-facing applications. You’ll set direction, strengthen the management layer and ensure teams deliver reliable products that create measurable customer value.
What you'll own
You'll lead the engineering teams behind our agentic research product and the applications customers use every day, through a group of engineering managers.
You'll be accountable for:
- Direction and structure: set the direction for application engineering within our engineering strategy; define team structure and the operating model; make the significant resourcing and structural decisions.
- Delivery: monthly plans that teams actually meet, built with Product on real capacity, with trade-offs made explicit when priorities change and progress visible to everyone; drive roadmaps and cross-functional technical programmes.
- Customer value: keep your teams focused on outcomes, not output. Understand the problems our customers' scientists are solving, check that what we ship gets used and makes a difference, and change or stop what doesn't.
- Quality and reliability: own the quality, security and operational health of what your teams ship, from release practice to incident response.
- People and culture: manage and coach engineering managers, build a strong management layer, own the hiring plan, and be accountable for the culture across your org.
- AI-first engineering: drive AI-first workflows across all your teams, invest in reusable tooling and enablement, and set standards and ROI targets for how we build with agents, from planning to code review to release.
- Partnership: work with VPs and Product leadership on what we build, and with Data, DevOps and Security on how it fits together; represent engineering externally in hiring.
Your impact is department-wide: you'll be part of the engineering leadership team, help shape engineering-wide decisions, and step in to lead engineering when needed.
What success looks like
- Teams plan on real capacity with Product and deliver predictably, in small increments.
- Every area has a clear owner, and teams are shaped around clear mandates.
- AI-first engineering is how the whole function works: from planning to automated testing, review and release.
- Your engineering managers grow, and the teams become a place strong engineers want to join and stay.
- Teams judge success by the value customers get, not the number of features shipped, and customers notice the difference release after release.
What we're looking for
You'll need
- 10+ years in software engineering and 4+ years leading engineering managers, ideally in a scale-up environment.
- A track record of predictable delivery: planning on real capacity, limiting work in progress, and saying no or making trade-offs with Product.
- A customer-first mindset: you measure your teams by the value they deliver, not the features they ship, and you bring engineers close to the customers they build for.
- Real experience leading teams that build with AI coding agents (Claude Code or similar), including how review, testing and quality change when agents write most of the code.
- Experience leading distributed teams across countries and time zones.
- Clear, direct communication with engineers, product leaders and executives.
How we'll assess you
- Leadership: broad engineering leadership across several sub-domains; a strategic thinker who can judge direction for areas you don't personally know in depth.
- AI fluency: you already embed AI in how your teams work, and you can take it to the next level for a whole function: AI-first workflows across teams, shared tooling, clear standards and measurable return.
Nice to have
- Experience leading teams that ship LLM, ML or other AI-powered features to production, with enough technical depth to challenge architecture and quality decisions.
- Life sciences, biomedical data or B2B SaaS for enterprise customers.
- Hands-on experience building agentic systems (multi-step agents, tool use, evaluation).
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.
Source: Causaly careers (Ashby)