At a Glance
- Tasks: Lead a team of applied scientists to deliver innovative AI solutions.
- Company: Join an exciting Glasgow start-up revolutionising trust in AI technology.
- Benefits: Competitive salary, comprehensive benefits, and continuous learning opportunities.
- Other info: Collaborative environment focused on growth and high standards.
- Why this job: Make a real impact in AI while working with cutting-edge technologies.
- Qualifications: 7+ years in tech, with experience managing applied science teams.
The predicted salary is between 80000 - 100000 £ per year.
COMPANY INTRODUCTION
Kodamai is an innovative early-stage Glasgow start-up built on the proposition that we can build AI agents you can actually trust with real work.
Not satisfied with agentic AI that is stitched together from scripts and hoped to behave, Kodamai uses formal methods (category theory, type theory, etc.) to create precise specifications for what an agent may do, and then constructs agents that provably meet those specifications.
Actions that fall outside the spec cannot be expressed, and each action carries evidence that it stayed within the rules it was given.
That rigour is what makes our agents suitable for regulated, high-stakes settings like healthcare, manufacturing and finance.
We pair original scientific research with a hands-on, high-trust team that ships — and we are growing fast.
If you want work that is both deeply principled and actually deployed, this is the place for you.
ROLE OVERVIEW
We are looking for an exceptional Senior Manager to bring operational excellence to our Applied Science team at Kodamai.
You will work together with our science and product leadership to set technical and scientific roadmap for a team of applied scientists and research engineers and then have ownership for executing against that roadmap with on-time production-quality deliverables.
You will own the day-to-day management of the team, driving delivery, sharpening processes, supporting career growth, and creating the structure and stability that let our scientists do their best work.
You will partner closely with our science leads, complementing their technical direction with the operational rigour and people leadership needed to scale a high-performing team.
You will collaborate closely with cross-functional teams, including research, engineering, product, and client delivery, to coordinate priorities, align timelines, remove blockers, and ensure the team delivers reliably against its commitments.
This is a senior, on-site leadership role based at our Glasgow headquarters.
KEY RESPONSIBILITIES
- Provide hands-on people management for a team of applied scientists and research engineers—setting clear goals, running regular 1:1s, giving feedback, and owning performance and career development.
- Own team planning and delivery, translating the science leadership's priorities into structured roadmaps, milestones, and clear ownership.
- Drive projects from prototype through to production, coordinating people, timelines, and cross-team dependencies to ship reliably.
- Establish and continuously improve the team's operating rhythm—planning, execution, code review, and delivery quality.
- Partner with product, engineering, and client-delivery teams to identify high-impact opportunities and deliver measurable outcomes.
- Represent the team's work to internal and external stakeholders, communicating complex scientific concepts clearly and persuasively.
- Support recruitment, onboarding, and professional development to build and retain world-class scientific talent.
QUALIFICATIONS & REQUIREMENTS
Education & Experience
- Degree in a technical or quantitative field (e. g. Computer Science, Engineering, Mathematics).
- 7+ years in technology or applied science environments, with an emphasis on agentic AI or automated reasoning
- 3+ years directly managing applied science teams, with clear ownership of people management, software process, and delivery.
- Proven track record of managing teams that deliver complex technical projects meeting customer needs reliably, on time, and to a high standard.
- Delivery and Operational Leadership
- Run an effective operating rhythm across one or more teams: sprint/kanban cadences, planning, and predictable delivery.
- Metrics-driven delivery: track and improve cycle time, lead time, deployment frequency, and error/quality rates.
- Estimation and predictability: hit commitments consistently, and understand and address the causes when you do not.
- Familiarity with scaling frameworks such as SAFe, or comparable models for coordinating delivery across teams.
- Invest in developer experience: faster onboarding, reproducible environments, and golden paths — templates, scaffolding, and tooling that increase ship speed without rework.
- Champion strong engineering practice: security-aware design reviews, secrets management as standard, and test-driven development to surface issues before demo or shipping.
- Technical Skills
- Enough working knowledge (or willingness to learn) of Kodamai’s domains — formal methods, automated reasoning, and neurosymbolic AI — to manage priorities, trade-offs, and delivery credibly.
You will not be setting the scientific direction.
- Comfortable engaging technically with the team and reading code.
- An understanding of how rigorous research and technical evaluation work, so you can support the team and hold it to a high standard.
- Able to guide a team in producing clean, maintainable, production-ready code, using modern delivery tooling (CI/CD, deployment, monitoring) on cloud infrastructure.
- Soft Skills
- Proven people-leadership skills, with the ability to inspire, mentor, and develop a technical team.
- Strong ability to understand customer point-of-view to ensure valuable science results in valuable products.
- Strong team player with excellent collaboration and interpersonal skills.
- Effective communicator, able to articulate complex technical concepts clearly.
- Self-motivated, detail-oriented, and capable of managing multiple priorities.
- Passion for driving high standards of scientific rigour and engineering quality across the team.
WHAT WE OFFER
- Competitive salary commensurate with experience, plus a comprehensive benefits package.
- Collaborative and growth-oriented work environment.
- Continuous learning opportunities and access to cutting-edge AI technologies.
HOW TO APPLY AND OUR ASSESSMENT PROCESS
Interested candidates are invited to submit their up to date CV (pdf) together with a brief cover note outlining their relevant experience and technical background to our HR department.
If we consider you a strong candidate for the role, we'll arrange a short initial interview, followed by a more in-depth technical interview with the team, where you'll be given a challenging problem to solve.
Please note, due to the volume of applications, we may only contact candidates who are being considered for further assessment.
SENIOR MANAGER, APPLIED SCIENCE in Milton employer: Kodamai
Kodamai is an exceptional employer that fosters a collaborative and growth-oriented work environment in the heart of Glasgow. With a focus on continuous learning and access to cutting-edge AI technologies, employees are empowered to drive high standards of scientific rigour and engineering quality. The company values operational excellence and offers meaningful career development opportunities, making it an ideal place for those looking to make a significant impact in the field of applied science.
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We think this is how you could land SENIOR MANAGER, APPLIED SCIENCE in Milton
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We think you need these skills to ace SENIOR MANAGER, APPLIED SCIENCE in Milton
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
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How to prepare for a job interview at Kodamai
✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
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✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.