How Condor is Building the Financial Intelligence Layer for Life Sciences

Condor has doubled in size since closing our $24 million Series A funding round in March. A lot of that investment is going into expanding our engineering team. The reason is simple: What we’re building at Condor is truly unique and has the power to transform life sciences R&D. Our Financial Intelligence Layer is powered by a knowledge graph and clinical and financial ontology that we developed over years with Big 4 accounting firms, giving life sciences R&D teams trustworthy data that empowers them to operate with confidence and bring therapies to patients faster and more cost effectively.

Having the best engineering team in the world isn’t a nice to have; it’s a must have. That’s why we’ve been obsessed with making our impressive engineering team even better. 

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Building the R&D infrastructure that all life sciences companies rely on

Jay Tailor recently joined Condor as VP of Engineering with 18 years experience building and scaling complex AI, data, and ML systems. The work he’s doing with the engineering team is critical to us delivering our clinical finance AI agents later this year. 

He spent nearly a decade at Unity Technologies, where he rose from engineering lead to director. During that time, he built the company's centralized data platform from the ground up (a streaming system that grew into critical infrastructure for the business, processing billions of events a day to power monetization and analytics); scaled teams from a handful of engineers to more than 60 people across AI, data, ML, and cloud; transitioned the platform to modern stream based processing; and partnered with Google for nearly two years to build machine learning infrastructure at a scale that most engineers never encounter.

I asked him why he left gaming for biopharma. He said: “A lot of AI companies right now are building generative tools. That's fine, but the field where AI is going to have the most transformative impact is life sciences and biopharma. I want Condor to be the Stripe of biopharma. The infrastructure that every top pharma and biotech company in the world relies on for their financial intelligence. The thing where there's no real alternative because Condor is just that good. That's what we’re all building toward.”

AI as a foundation, not a feature

To do that, AI can’t be a bolt on. At Condor, everything a customer touches — from onboarding, to exploring their data, to understanding why a number changed, to seeing what's really happening across a trial — is intelligent by default. Jay says, "We are incorporating AI into our Financial Intelligence Layer in a way that makes you stop and think, how did we ever do this without Condor?"

That same conviction runs through how the team works. AI is embedded across the full development lifecycle. That enables engineers to spend their time on the hard, high-value problems that actually move the mission forward. 

The engineering team we're building

We're looking for engineers who are driven to solve  hard problems at the intersection of data and AI. In particular, people who bring:

• Deep data experience — building and scaling data platforms, pipelines, and systems where accuracy and trust are non-negotiable.
• Strong backend engineering — designing services and architectures built to scale, with a high bar for craft and reliability.
• Production AI-agent experience — not demos or prototypes, but AI agents shipped into real production environments, solving real problems for real users.
• FDE (Forward Deployed Engineer) – hybrid software engineer, technical consultant, and product manager. They embed directly with customers, usually on-site, to implement, customize, and troubleshoot technical platforms (especially AI and LLM products)

Beyond the technical requirements, we also look for a particular mindset: someone who moves fast, but builds things that last. It takes a deep love of the craft to build something extraordinary. Someone who is energized by real stakes since our infrastructure helps get medicines to patients faster. Someone who wants AI to be part of how they work every day. And above all, someone who is curious: they want to know why we're building something, who we're building it for, and what their paint points are. 

Our culture reflects that. We move with urgency, because we have a real window to define this category. We hold a high bar for quality and craft. We start from the customer's real problem; not the feature request. A culture where wins are shared and celebrated.

If that resonates, we're hiring. Learn more here.