Ml/ai Cloud Engineering Architect

**Introduction to role**

Are you ready to be part of the future of healthcare? Do you have the vision to harness digital and AI to tackle life sciences challenges? Evinova, a separate business within the AstraZeneca Group, might be your next adventure Transform billions of patients' lives through technology, data, and innovative ways of working. If you're disruptive, decisive, and transformative, eager to use technology to improve patients' health, join us at Evinova. We deliver market-leading digital health solutions that are science-based, evidence-led, and human experience-driven. Smart risks and quick decisions accelerate innovation across the life sciences sector. Be part of a diverse team pushing the boundaries of science by digitally empowering a deeper understanding of the patients we’re helping. Launch game-changing digital solutions that improve patient experiences and deliver better health outcomes. Together, we combine deep scientific expertise with digital and artificial intelligence to serve the wider healthcare community and create new standards across the sector. The Machine Learning and Artificial Intelligence Operations team (ML/AI Ops) is newly formed to spearhead the design, creation, and operational excellence of our entire ML/AI data and computational AWS ecosystem to catalyze and accelerate science-led innovations.

**Accountabilities**

This team is responsible and accountable for the design, implementation, deployment, health and performance of all algorithms, models, ML/AI operations (MLOps, AIOps, and LLMOps) and Data Science Platform. We manage ML/AI and broader cloud resources, automating operations through infrastructure-as-code and CI/CD pipelines, and ensure best-in-class operations - striving to push even beyond mere compliance with industry standards such as Good Clinical Practices (GCP) and Good Machine Learning Practice (GMLP).

As the ML/AI Cloud Engineering Architect on our team, you will architect and oversee the global cloud ML/AI infrastructure that underpins our entire ML/AI value proposition. You will design, implement, and manage scalable cloud solutions using AWS services while establishing ML/AI governance frameworks, automating infrastructure with tools like AWS CDK and Projen, and conducting cost-benefit analyses of foundation models to drive strategic decisions across the organization.

This position requires a deep understanding of cloud-native ML/AI Ops methodologies and technologies, AWS infrastructure, State-of-the-art (SOTA) Foundation Models and AWS GenAI Services, and the unique demands of regulated industries, making it a cornerstone of our success in delivering impactful solutions to the pharmaceutical industry.

**Role & Team**Key Responsibilities**:
Operational Excellence
- Lead by example in creating high-performance, mission-focused and interdisciplinary teams/culture founded on trust, mutual respect, growth mindsets, and an obsession for building extraordinary products with extraordinary people.
- Drive the creation of proactive capability and process enhancements that ensures enduring value creation and analytic compounding interest.
- Design and implement resilient cloud ML/AI operational capabilities to maximize our system A-bilities (Learnability, Flexibility, Extendibility, Interoperability, Scalability).
- Drive precision and systemic cost efficiency, optimized system performance, and risk mitigation with a data-driven strategy, comprehensive analytics, and predictive capabilities at the tree-and-forest level of our ML/AI systems, workloads and processes.

ML/AI Cloud Operations and Engineering
- Architect and implement scalable AWS ML/AI cloud infrastructure in a multi-tenant SaaS environment.
- Establish governance frameworks for ML/AI infrastructure management and ensure compliance with industry best practices.
- Ensure principled and methodical validation pathways and a Well Architected Framework for Embryonic Research (WAFER) similar to and building on AWS’s Well Architected Framework (WAF) for all early stage product and operational GenAI PoC’s across the organization.
- Oversee ML/AI related Kubernetes (k8s) cluster management and provide expertise on alternative ML/AI workflow orchestration options such as Argo vs Kubeflow, and ML/AI data pipeline creation, management and governance with tools like Airflow.
- Employ AWS CDK (TypeScript), Projen, and Argo CD to automate infrastructure deployment and management.
- Help set the strategy and manage the tactical balance between framework and platform experimentation and democratization with standardization and centralized management and governance.
- Conduct cost-benefit analyses and formal processes for selection and utilization of foundation models, evaluating their architectures, performance, and costs.
- Work with multiple teams to ensure that the platform meets organizational needs and scales effectively.

Personal Attributes:

- Customer-obsessed and passionate about building pr