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The role involves supporting customer engagements, optimizing operational models, and assisting in improving business performance in the Life Sciences industry through a structured consulting program.

This role involves supporting customer engagements, collaborating with consultants to optimize processes, and leveraging Veeva's technology to deliver solutions in the Life Sciences industry.

The role involves supporting client engagements in Life Sciences, focusing on operational improvement strategies through data and consulting. Candidates will own workstreams and collaborate on business solutions.

The role involves supporting customer engagements, delivering business solutions, and collaborating with team members to improve customer operations in the Life Sciences industry.

The role involves supporting customer engagements, collaborating with teams to create deliverables, and leveraging Veeva's software for operational improvement in the Life Sciences sector.

Manage end-to-end SaaS implementations for Veeva Ostro (6–12 week projects), coordinate cross-functional teams, configure applications with a no-code flow builder, perform QA, prepare regulatory annotations, identify and mitigate risks, and maintain client communication to ensure on-time go-lives.

Lead design and implementation of cloud-native DevOps for a new AI-driven platform. Build IaC, CI/CD pipelines, automate deployments, provision and scale infrastructure, improve reliability, and drive engineering best practices and mentorship.

Lead DevOps engineering for a new AI-driven life sciences platform: design cloud architecture, implement IaC, build CI/CD pipelines, manage Kubernetes/OpenShift and serverless infrastructure, improve reliability and performance, and mentor the growing engineering team.

Lead design and implementation of cloud-native infrastructure and DevOps practices for a new AI-driven life sciences platform. Build IaC, CI/CD pipelines, and automated deployments; manage and scale infrastructure with Ansible, Terraform, and Kubernetes; improve reliability, performance, and operational risk; mentor engineers and drive architectural best practices.

Lead DevOps for a new AI-driven life sciences platform: design cloud architecture, implement IaC and CI/CD, manage infrastructure (Ansible, Terraform, Kubernetes/OpenShift), improve reliability, and mentor a growing engineering team to deliver production customers within the first year.