cosine - Founding Healthcare Lead

London, England, United Kingdom+ Equity2w ago

In Office Staff EMEA Pharmaceuticals Biotechnology Tech Lead Market Research Go-to-market Strategy Data Governance

Requirements

• We're open-minded about backgrounds, but expect the successful candidate to combine deep healthcare industry knowledge with exceptional commercial judgement and entrepreneurial drive. • Significant commercial, strategic or operational experience in healthcare, pharmaceuticals, biotechnology or life sciences. • A strong understanding of how major healthcare organisations operate, buy technology and make investment decisions. • A track record of building senior relationships and turning complex opportunities into commercial outcomes. • The ability to engage credibly with both technical and non-technical stakeholders, from researchers and engineering teams to senior executives. • Strong commercial instincts, including the ability to identify genuine customer problems, develop business cases and negotiate complex deals. • Genuine enthusiasm for AI and a strong understanding of its emerging capabilities and limitations. • High levels of independence, ownership and comfort operating in an early-stage, fast-moving environment. • Particularly interesting • Experience commercialising AI, machine learning, data platforms or other advanced technologies within healthcare. • An established network across pharmaceutical companies, biotechnology firms, NHS organisations, healthcare technology providers or research institutions. • Experience with bespoke model development, AI infrastructure or enterprise AI deployments. • Familiarity with healthcare data governance, clinical safety, information security and relevant regulatory frameworks. • Experience building a new business line, entering a new market or taking an emerging technology from initial concept to significant revenue. • A background spanning both technical and commercial roles. • ___________________________________________________________________________

Responsibilities

• Build our healthcare business • Define and execute Cosine's go-to-market strategy across healthcare, pharmaceuticals, biotechnology and the wider life sciences ecosystem. • Identify the highest-value applications for Cosine's technology, particularly where generic AI solutions fall short. • Establish relationships with senior leaders across healthcare providers, pharmaceutical companies, research institutions and technology partners. • Build and own a pipeline of significant commercial opportunities, from initial engagement through to contracts and long-term partnerships. • Shape high-impact AI opportunities • Work with customers to identify complex problems that could benefit from bespoke AI models, agentic systems or autonomous software engineering. • Translate customer needs into clear technical and commercial proposals, working closely with Cosine's ML and engineering teams. • Structure and negotiate commercial agreements spanning pilots, bespoke model development, enterprise licensing and strategic partnerships. • Help customers navigate the practical challenges of deploying AI in healthcare, including data governance, security, regulatory requirements and integration with existing systems. • Build the foundations of a new vertical • Develop a deep understanding of where Cosine can establish a differentiated position in healthcare. • Represent Cosine at industry events, executive meetings and strategic discussions. • Feed market insights back into our research and product roadmap, helping us prioritise the capabilities with the greatest commercial potential. • Work across the organisation to ensure that customer engagements translate into successful deployments and sustainable long-term relationships. • As the business grows, help build the team, partnerships and operating model required to scale the vertical. • ___________________________________________________________________________

Benefits

• Work at the frontier of AI. We're not simply integrating third-party AI models. We're building and training our own models, developing the infrastructure to deploy them, and creating the agentic systems that make them useful.