1. Act as a force multiplier for the CTO by translating priorities and expectations into concrete actions, deliverables, and timelines.
2. Reduce iteration overhead by working with owners across engineering and product teams to clarify next steps, raise quality, and ensure outputs meet expectations before CTO review.
3. Proactively identify where work is getting stuck and drive progress through structured proposals, clear scoping, and follow-through.

1. Own preparation for technical customer meetings, including:

   • Understanding end-to-end technical stacks and (machine learning) workflows.
   • Creating clear, compelling customer-facing narratives and presentations.
   • Coordinating inputs across teams.

2. Ensure strong follow-ups after customer meetings:

   • Coordinate internal ownership and track execution.
   • Prepare materials and agendas for subsequent sessions.

3. As soon as possible: be able to run technical

   customer meetings, bringing in subject-matter experts as needed and ensuring high-quality outcomes.

1. Keep cross-functional product and engineering initiatives moving by:
   • Clarifying goals and expected outputs.
   • Helping owners break down complex tasks into actionable steps.
   • Proposing initial drafts (e.g., architecture diagrams, workflows, or outlines) to accelerate feedback and decision-making.
2. Support process improvements that increase execution speed and clarity, while respecting clear ownership boundaries.

1. Enable teams through shared frameworks, templates, and best practices to improve alignment, speed, and quality across technical and product work.
2. Contribute to customer-facing materials, proposals, and internal documents to raise overall quality.
3. Translate high-level feedback into concrete improvements in preparation, narrative, and execution.

1. Support early scoping of new opportunities or special projects by
   • Structuring initial workflows and technical approaches.
   • Coordinating early inputs from product, engineering, and computational drug discovery.

Strong technical background (e.g. computer science, engineering, sciences, or related field) with the ability to understand and communicate complex systems end-to-end, across infrastructure, ML models, data flows, and product workflows.

2-7+

years of experience in fast-paced, high-output environments such as strategy consulting (e.g., MBB), venture capital, or high-growth startups or scaleups.

Ability to build a solid working understanding of the full technical stack and communicate effectively with infrastructure engineers, ML engineers, scientists, and product managers.

Strong capability to distill complex and fragmented technical input into clear summaries, structured options, and decision-ready recommendations for leadership and customers.

Comfort operating across levels of abstraction, from high-level system architecture and workflows to concrete implementation approaches and technical assumptions.

Ability to operate with ambiguity, proactively propose initial solutions, and use structured drafts (e.g. architecture diagrams, workflows, outlines) to accelerate alignment and progress.

Strong proficiency in core tools, including Atlassian suite, PowerPoint, product prototyping tools like Lovable/Bolt and ability to build high-quality materials fast, using modern AI and productivity tools.

Excellent execution skills, organization, and attention to detail, with a strong ownership mindset and focus on outcomes rather than tasks.

High ownership mindset; you take responsibility for outcomes, not just tasks.

Excellent written and verbal communication skills, with confidence in customer-facing settings. English: C2 level; German optional.

Comfort working in a remote-first environment across distributed teams.

Curiosity and willingness to learn about AI-driven drug discovery, the broader life sciences ecosystem, and Apheris’ customers .