Principal AI Support Engineer

We are seeking a Principal AI Support Engineer to join our AI Support Team. The ideal candidate will have industry-relevant experience delivering at scale Machine Learning or Data Science in the AWS cloud ecosystem.

The AI Support Team is responsible for supporting the level 1 and 2 post-production activities in the Enterprise AI team. As a Principal AI Support Engineer , you will be the first respondent for any issues/requests raised post-production by users of the Enterprise AI Services.

The Enterprise AI team aims to fulfill AstraZeneca’s ambition to use AI in every step of the value chain, from discovering new compounds to patient safety systems. The enterprise AI team consists of 3 verticals: Connected Intelligence, Reusable AI and AI Platforms, and AI Support. The verticals deliver the AI app store, AI models and ready-to-use platforms to data scientists across AZ. The AI support team will attend to the post-production activities of the 3 verticals.

We achieve this through technical leadership and agile-focused development, continuously evaluating the fast-moving advancements in Machine Learning tooling for challenges across AstraZeneca’s R&D, Commercial and Operations domains.

You will be part of a collaborative team of multidisciplinary engineers and together have the chance to work on tools that will advance the standard of healthcare, improving the lives of millions of patients across the globe. Our data science platforms will support major AI initiatives such as clinical trial data analysis, knowledge graph analytics, patient safety systems, deep learning-led drug discovery, and software as a medical device system.

Key Accountabilities

1. Collaborate with Data Scientists and Machine Learning Engineers from across the company to understand their challenges. You will need to work with them to triage and resolve issues ranging from developmental to production.
2. Be a part of an impactful agile team, continuously improving AstraZeneca’s AI support offering and tooling.
3. Work closely and collaboratively with internal governance and compliance functions such as Cyber Security and Data Privacy to establish and work within security guardrails without obstructing end-user productivity.
4. Adapt standard machine learning methods to best exploit modern parallel environments (e.g. distributed clusters, multicore SMP, and GPU), to guide ML engineers during their use of AI platforms.
5. Champion a “production first” approach to ensure the vital support for infrastructure and platforms is available to scale exploratory research to production.

Candidate Knowledge, Skills and Experience

1. BSc/MSc/PhD in Computer Science or a related quantitative/analytical field.
2. 10+ years of experience in a similar role, with a focus on managing AI platform support, preferably in a large-scale enterprise environment.

Strong understanding of:

1. Cloud computing platforms (e.g., AWS, Azure, GCP).
2. Containerization technologies (e.g., Docker, Kubernetes).
3. AI frameworks (e.g., TensorFlow, PyTorch).

Experience with:

1. Kubernetes and/or container-based application deployments.
2. Administering a production cluster, including the understanding of operators, storage classes, and service meshes.
3. Building and delivering software using Python and other programming languages.
4. DevOps/MLOps/AIOps practices and tools for automation, configuration management, and CI/CD (e.g., Git, Terraform, Python).
5. Deploying the underlying infrastructure and tooling for running Machine Learning or Data Science at Scale using Infrastructure as Code.
6. Using DevOps to enable automation strategies - Agile collaboration, with knowledge or experience in product or platform-focused delivery.
7. Data science/ML journey, from model experimentation to industrialization.
8. Internal security standards and frameworks, especially in medical, clinical, or pharmaceutical contexts.
9. GxP-compliant life science systems.
10. Excellent problem-solving skills, with the ability to analyze sophisticated issues, prioritize tasks, and drive resolution in a fast-paced environment.
11. Strong communication and interpersonal skills, with the ability to collaborate effectively with cross-functional teams and influence stakeholders at all levels.
12. Experience in mentoring and managing junior team members.
13. Creative, collaborative, and resilient.

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.

Ready to make an impact? Apply now to join our team and help us improve lives across the world!