Associate Principal AI Engineer - Mathematical Optimisation
About this opportunity
Role: Associate Principal AI Engineer - Mathematical Optimisation
Location: Cambridge UK
Salary: Competitive + Excellent Benefits
Do you have expertise in, and passion for Operations Research and AI? Would you like to apply your modelling expertise in a company that follows the science and turns ideas into life changing medicines? Then AstraZeneca might be the place for you!
Disrupt an industry and change lives
At AstraZeneca, we are committed to being a great place to work, where people are empowered to push the boundaries of science and make a meaningful impact on patients, medicine, and society. We foster an inclusive culture built on diversity, collaboration, and continuous learning.
In technology, you will be encouraged to take ownership, challenge the status quo, and drive innovation. By enabling the business to operate faster and more effectively, you will help deliver solutions that ultimately improve lives around the world.
What you’ll do
The ideal candidate will bring proven experience in designing, developing, and supporting end-to-end AI and optimisation solutions across a broad range of business challenges.
This role offers the opportunity to work on some of the most complex and high-impact AI and optimisation engineering problems in the pharmaceutical industry. As part of a global team of AI engineers, data scientists, scientists, and software developers, you will help design, build, and support tools that transform how AstraZeneca operates at scale, improving efficiency in our mission to benefit millions of patients worldwide.
You will work closely with engineering and product teams to deliver and support scalable solutions within the AstraZeneca technology landscape, while championing software engineering best practices across the organisation.
We are looking for an engineer who can build and maintain robust, accurate, and reliable end-to-end AI solutions used across AstraZeneca. You should be comfortable working with complex systems and applying AI and optimisation at scale to drive productivity and business impact.
Key Accountabilities
Contribute to design and development of end-to-end AI solutions that include mathematical optimisation, modelling, and simulation approaches.
Visualise complex datasets and model outputs using the latest front-end technologies.
Work together with senior optimisation engineers and AI engineers in the team, focused on product delivery and support.
Liaise with other engineers to enhance our technological stack, to enable the adoption of the latest advances in AI and software engineering.
Contribute to various solutions and applications that may cover a broad range of business areas, sometimes at once.
Be self-driven, curious, innovative, deeply technical and learn continuously.
Essential for the role
Experience and demonstrable technical skills in developing operations research solutions for complex real-world problems.
Demonstrated experience using mathematical optimisation software such as CPLEX, Gurobi, SCIP, or OR-Tools.
Experience with heuristic and meta-heuristic algorithms as an alternative to the above software.
A working knowledge of optimisation, simulation, and statistical concepts.
A working knowledge of LLM tools.
Experience in good software development practice, ideally including Python, and deployment practices such as CI/CD, testing, version control.
A track record of understanding and translating complex business challenges into well-defined engineering problems.
Creative, collaborative, & product focused.
MSc or above.
Desirable for the role
Experience of adjacent topics such as control and robotics.
Experience in the deployment of AI tools.
Experience in developing and deploying interactive applications (e.g., full-stack apps, dashboarding).
So, what’s next?
Be part of something where your work directly impacts a big purpose: to develop life-changing medicines. Join Us!
Where can I find out more?
Our Social Media,
Follow AstraZeneca on LinkedIn https://www.linkedin.com/company/1603/
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When we put unexpected teams in the same room, we unleash bold thinking with the power to inspire life-changing medicines. In-person working gives us the platform we need to connect, work at pace and challenge perceptions. That’s why we work, on average, a minimum of three days per week from the office. But that doesn't mean we’re not flexible. We balance the expectation of being in the office while respecting individual flexibility. Join us in our unique and ambitious world.
#LI-HYBIRD
Date Posted
05-Nov-2026
Closing Date
20-Nov-2026
Our mission is to build an inclusive and equitable environment. We want people to feel they belong at AstraZeneca and Alexion, starting with our recruitment process. We welcome and consider applications from all qualified candidates, regardless of characteristics. We offer reasonable adjustments/accommodations to help all candidates to perform at their best. If you have a need for any adjustments/accommodations, please complete the section in the application form.
Job details
How this role compares
Computed from every other active Data & Digital role in our database, not just this employer's listings.
We currently track 227 comparable Principal Data & Digital roles across 48 biopharma companies.
Salary context
69 of 227 peers report a salary range (USD, annualized)
Peers share this role's job function and a matching or adjacent seniority level -- not necessarily the same therapeutic area or country.
Where these roles are based
Top locations among the 227 comparable roles
+ 18 more countries
Seniority mix
227 of 227 peers have a known seniority level
Therapeutic area mix
3 of 227 peers have a known therapeutic area; the rest are genuinely unlabeled, not hidden
Similar opportunities
The closest matches from our peer group, ranked by how similar they are, not how well you'd qualify for them -- treat this as market context, not a guaranteed shortlist; a weak match is labeled as one below.
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How we calculate "similar"
No black box, no LLM guesswork: a deterministic score built from four normalized attributes. Here's this role's own peer group at different match levels, so you can see the mechanism, not just the result.
Every comparison starts from the same 100-point budget: 25 for working in the same function, 40 for the same therapeutic area, 20 for the same or adjacent seniority, 15 for the same country. A dimension we can't confirm on both sides contributes nothing, never a guess, never a free pass.
0 points, never a partial guess. A role we know almost nothing about beyond its function bottoms out at 25%; it never inflates to 100% just because there's little to compare against. Seniority uses a defined ladder (Associate → Manager → Associate Director → Senior → Principal → Director → Senior Director → Executive/VP) so "Director" and "Senior Director" count as adjacent, but "Director" and "Executive/VP" do not.