Introduction to the Role
Are you ready to engineer a secure, agentic multi-cloud platform that accelerates life-changing medicines to patients? In this role, you will evolve beyond traditional infrastructure by building governed agents, reusable cloud capabilities and human-in-the-loop controls that let teams move faster without compromising safety. Your work will turn complex requirements into clear, automated patterns that are identity-aware, policy-controlled, observable and auditable.
You will join a hands-on engineering group operating across AWS, Azure and Google Cloud, working in agile squads to ship self-service products that reduce cycle time from weeks to hours. You will lead initiatives, mentor peers and own outcomes end to end. Can you picture guiding an agent from plan to approved change with full traceability, while keeping humans in control?
Your platform will power data, AI and research workloads, including GPU-accelerated inference and analytics. By integrating agentic tools with enterprise standards, you will help scientists and engineers focus on discovery while the platform quietly delivers speed, reliability and compliance at scale.
Accountabilities
•Multi-Cloud Landing Zones: Design and operate enterprise-grade landing-zone and platform capabilities across AWS, Azure and GCP to provide secure, scalable foundations for product teams.
•Reusable Infrastructure and Policies: Develop reusable Infrastructure as Code and Policy as Code that embed security, data residency, encryption, tagging, cost and compliance requirements, raising our default bar.
•Self-Service and Agentic Products: Build secure self-service products and governed agents for environment creation, workload onboarding, migration, lifecycle management and decommissioning to cut lead times and reduce toil.
•Agentic Platform Architecture: Contribute to the Agentic Cloud platform architecture, product catalogue and multi-cloud portability model to drive consistent patterns and adoption.
•Agent and MCP Design: Design agents and MCP tools with explicit schemas, least-privilege permissions, versioning, ownership, lifecycle status and support routes so teams can safely consume capabilities.
•Secure Integrations: Integrate workflows with IAM/OIDC, RBAC, secrets management, CI/CD, ITSM, observability, knowledge bases and systems of record to enable end-to-end automation.
•Human-in-the-Loop Controls: Implement approval gates for sensitive agent actions, ensuring models select capabilities but never grant access, keeping humans in control where required.
•Observability and Audit: Maintain end-to-end traces, evaluation results and audit records for agent plans, tool calls and infrastructure changes to prove compliance and speed incident learning.
•Accelerated AI Workloads: Enable GPU and accelerator workloads by selecting appropriate compute, optimizing utilization and supporting scalable inference patterns for research and analytics.
•Telemetry and AIOps: Build telemetry and AIOps for availability, performance, cost, security and agent behavior across the three cloud providers to drive proactive operations.
•Partnership and Influence: Partner with security, architecture, FinOps, application, data and research teams to translate requirements into reusable platform products that deliver measurable outcomes.
•Technical Leadership: Lead technical initiatives, coach engineers and contribute to standards, design reviews, incident learning and continuous improvement, scaling your impact across squads.
Essential Skills and Experience
•Deep engineering experience in at least one of AWS, Microsoft Azure or Google Cloud, with working knowledge of the services, identity models and networking patterns of the other two.
•Hands-on experience with cloud landing zones, organizations/subscriptions/projects, network connectivity, private endpoints, DNS, IAM, encryption, secrets and centralized logging.
•Strong Infrastructure as Code capability using Terraform; experience with native frameworks such as AWS CloudFormation/CDK, Azure ARM or other IaC tools is beneficial.
•DevOps and software engineering practices using GitHub, GitHub Actions, automated testing, artifact management, code review and release controls.
•Observability and reliability engineering using metrics, logs, traces, service-level objectives, incident response and automated remediation.
•Programming and scripting with Python and at least one of TypeScript/Node.js, Go or similar languages; ability to develop and consume APIs.
•Agent engineering: define specialist agents with clear goals, bounded actions, deterministic tool contracts, context management, error handling and testable acceptance criteria.
•MCP engineering: publish and consume enterprise, partner and cloud-provider MCP servers; define stable tool schemas, authentication, authorization, versioning and observability.
•Understanding of responsible AI infrastructure controls, including data residency, encryption, model and tool access, evaluation, auditability and fallback behavior.
•Amazon Bedrock/AgentCore, Azure AI Foundry/Azure OpenAI, Google Vertex AI or equivalent managed AI platforms.
Desirable Skills and Experience
•Agent frameworks such as LangGraph, Strands Agents or comparable orchestration technologies.
•FinOps practices for chargeback/showback, unit economics, optimization and AI/GPU cost visibility.
•Cloud migration and modernization, including application assessment, platform onboarding and legacy workload transformation.
•Regulated-industry engineering, including GxP-aware controls, privacy, records, audit, resilience and data-residency requirements.
•Professional-level certification in AWS, Microsoft Azure, Google Cloud, Kubernetes, security or FinOps.
Our Approach to Working
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.
Why AstraZeneca?
Here, engineering excellence meets scientific purpose. You will be trusted to take ownership and push boundaries with leading technologies, from multi-cloud platforms to agentic systems, backed by investment, mentorship and a collaborative network of experts.
We bring diverse minds together to spark bold ideas, run real experiments and scale what works, all in a modern environment that prizes high standards, curiosity and transparency. Your contribution will speed how insights become therapies, and you will grow through hands-on challenges, peer learning and events that encourage exploration.
We value kindness alongside ambition and empower you to design solutions that are both innovative and responsible.
Ready to Make Your Mark?
If you are ready to lead the evolution of a secure, agentic multi-cloud platform and turn complex ideas into trusted capabilities that accelerate patient impact, step forward and make your mark today!
Date Posted
12-nov-2026
Closing Date
26-nov-2026
AstraZeneca embraces diversity and equality of opportunity. We are committed to building an inclusive and diverse team representing all backgrounds, with as wide a range of perspectives as possible, and harnessing industry-leading skills. We believe that the more inclusive we are, the better our work will be. We welcome and consider applications to join our team from all qualified candidates, regardless of their characteristics. We comply with all applicable laws and regulations on non-discrimination in employment (and recruitment), as well as work authorization and employment eligibility verification requirements.