Cloud Security Architect

PROJECT INFORMATION:

Industry: Healthcare/ Pharmacy

Start: ASAP (flexible).

Rate: depending on experience.

Contract: B2B 12 months + prolongations.

Remote: up to 100%

Location:  remote/ Warsaw.

Project language: English.

Business trips: some occasional included.

Recruitment process:  2 interviews.

Job Description

We are looking for a Staff Cloud Security Architect, AI Solutions to design and enable secure Azure-based architectures for AI applications that consume enterprise data from platforms such as Databricks.

This is a hands-on role for someone who can define architecture, security patterns, and technical standards while also working directly with engineering teams to implement them. The role is not primarily a Databricks platform architect role; the focus is on secure cloud architecture, AI application infrastructure, DevOps modernization, and compliant engineering foundations.

The architect will help teams build secure, scalable, and well-governed AI-enabled applications on Azure. This includes patterns for AI agents, sandboxed code execution, runtime isolation, network segregation, secrets management, CI/CD, Terraform, and GitHub Enterprise.

This role owns architectural design and technical standards but is not accountable for platform or application delivery.

The applications are currently non-GxP, but the architecture should support future GxP validation through traceability, controlled releases, documentation, and audit-ready engineering practices.

Significant experience in cloud architecture, cloud security architecture, platform engineering, or senior cloud engineering roles is required. The role demands proven hands-on experience designing and implementing secure Azure solutions and supporting engineering teams in building production-ready cloud applications.

Main Responsibilities

• Design secure Azure cloud architectures for AI applications, data-driven applications, and internal digital products.

• Define architecture patterns for AI applications that consume data from Databricks and other enterprise data platforms.

• Establish secure patterns for AI agents, sandboxed Python/code execution, runtime isolation, network segregation, and controlled access to data and services.

• Design and implement standards for secrets management, identity, access control, encryption, logging, monitoring, and secure connectivity.

• Use Terraform to define, review, and enable repeatable cloud infrastructure patterns.

• Help drive the migration from Azure DevOps to GitHub Enterprise.

• Establish new GitHub-based CI/CD patterns, including repository standards, branching, pull requests, code reviews, automated testing, approvals, deployment gates, and release evidence.

• Define technical standards for secure software delivery, release traceability, and audit-ready engineering practices.

• Partner with engineering teams to implement reference architectures, reusable templates, pipelines, and secure cloud patterns.

• Review solution designs, identify security risks, and guide teams toward practical, compliant, and maintainable implementations.

• Collaborate with cloud, security, data, AI, quality, compliance, and product teams.

• Mentor engineers and improve engineering practices across cloud, security, DevOps, and AI infrastructure.

Key Requirements

• Strong hands-on experience with Microsoft Azure cloud architecture.

• Strong cloud security expertise, including identity, networking, encryption, secrets management, logging, monitoring, and secure access patterns.

• Experience designing secure infrastructure for AI applications, AI agents, APIs, data-consuming applications, or internal developer platforms.

• Experience with sandboxed code execution, Python runtime environments, containerized workloads, or isolated compute patterns.

• Strong knowledge of network segregation, private endpoints, firewalls, virtual networks, controlled egress, and runtime isolation.

• Strong experience with Terraform for infrastructure provisioning and cloud architecture enablement.

• Strong experience with GitHub Enterprise, GitHub Actions, repository governance, branch protection, pull requests, and secure CI/CD patterns.

• Experience with Azure DevOps, ideally including migration from Azure DevOps to GitHub.

• Experience with secrets management, key vaults, managed identities, service principals, RBAC, and Microsoft Entra ID.

• Understanding of secure software delivery, release controls, traceability, and audit-ready engineering practices.

• Ability to work hands-on with engineers while also setting architecture direction and technical standards.

• A Bachelor’s degree in Computer Science, Software Engineering, Information Technology, Cybersecurity, Engineering, Mathematics, or equivalent practical experience is mandatory.

Nice to Have

• Experience with Azure AI services, Azure OpenAI, agent frameworks, or secure GenAI application patterns.

• Experience with Databricks as a data source for downstream applications.

• Experience with containers, Kubernetes, Azure Container Apps, Azure Functions, or similar runtime platforms.

• Experience with GitHub Advanced Security, code scanning, secret scanning, dependency scanning, or policy-as-code.

• Familiarity with life sciences, pharmaceuticals, healthcare, or another regulated industry.

• Understanding of GxP, CSV, CSA, SDLC controls, or validation documentation, especially for future validation readiness.

• Preferred Master’s degree in a relevant technical field, along with certifications like Microsoft Certified: Azure Solutions Architect Expert, Microsoft Certified: Azure Security Engineer Associate, Microsoft Certified: DevOps Engineer Expert, GitHub Actions or GitHub Advanced Security certification, and HashiCorp Terraform certification.