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…