Lead AI Engineer

The next wave of enterprise software won’t be dashboards or copilots.

It will be Digital Workers, autonomous AI systems capable of executing complex workflows end-to-end. At causaLens, we are building the platform that enables enterprises to deploy these Digital Workers safely and at scale.

Our Digital Worker Factory allows organizations to design, deploy, and manage AI agents that automate decision-making, analytics, and operational workflows across the enterprise. These systems are already being used by global companies including Johnson & Johnson, Syneos Health and Cisco to transform how work gets done.

We are particularly focused on pharmaceutical and life sciences organizations, where AI is rapidly becoming the operating system for commercial analytics, forecasting, regulatory workflows, and medical intelligence.

Backed by $50M+ in funding from Molten Ventures, Dorilton Capital, and IQ Capital, and supported by visionary investors including the CEO of Revolut, causaLens is scaling rapidly. Our team includes leading AI researchers, engineers, and scientists, almost 20% with PhDs.

Here are 2 articles that define our culture:
1. A Hiring Framework for a New Kind of Services Company

2. The Primacy of Winning

We’re hiring a Lead AI Engineer to design and deliver enterprise-grade AI systems and digital workers in production. You’ll work closely with global organisations, embedding with clients to untangle complex workflows and translate them into reliable, scalable agentic systems—integrating models, data, and enterprise infrastructure into solutions that operate in real-world environments.

We’re looking for experienced lead engineers who can own end-to-end delivery ofvadvanced AI systems. You’ll work across LLMs, multi-agent coordination, retrieval andvreasoning, and enterprise data integration; driving the development of systems that automate workflows and execute real business tasks at scale.

Our stack typically includes Python, modern LLM frameworks, orchestration tools, and cloud platforms such as AWS, GCP, or Azure.

• Deep, hands-on experience building and deploying production-grade AI systems using LLMs, RAG pipelines, MCPs, and agentic workflows

• Proven track record of leading complex, client-facing engagements with a forward-deployed mindset, partnering with both technical and business stakeholders

• Strong system design and architecture expertise, with the ability to translate ambiguous business challenges into scalable, reliable AI solutions

• Experience guiding technical projects, setting technical direction, and driving delivery to measurable outcomes

• Solid understanding of evaluation, reliability, and performance considerations in production AI systems

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  Work directly with enterprise clients to understand complex operational and analytical workflows

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  Translate ambiguous business challenges into clear technical strategies and system designs

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  Design scalable AI architectures and agentic systems combining LLMs, multi-agent orchestration, and knowledge retrieval

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  Break down initiatives into structured engineering plans and drive execution across teams

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  Lead technical delivery end-to-end, from architecture through production deployment and iteration

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  Guide engineers through implementation decisions and provide strong technical leadership throughout delivery

Our culture values intellectual rigour, ownership, and the primacy of winning. We expect team members to work from the office 1-2 days per week.