Head DDIT ISC Software Development Governance, Integrity & Secure Software Development Life Cycle (SDLC)

Job Description Summary We build and buy software that touches clinical trials, patient safety, manufacturing, quality systems and commercial operations. It now ships weekly rather than yearly, is increasingly AI-assisted, and increasingly contains AI. Our control framework was built for a slower world. This role makes secure, compliant, audit-ready software delivery the fastest path for engineers — not a gate they route around. You will own the enterprise SDLC governance model and build much of it yourself: policy as code, automated evidence capture, pipeline controls and reference architectures. This is a hands-on, individual-contributor leadership role. You will set enterprise direction, influence hundreds of engineers and lead through a federated community — but you will not have a large direct team, and you will spend meaningful time in repositories, pipelines and control code. Candidates seeking pure oversight or people management should not apply. Job Description Key Responsibilities: Own the enterprise policy, standards and controls for software engineering, including source control, branching, peer review, testing, release management, environment segregation, change control, configuration and release documentation. Rationalise overlapping GxP, SOX, privacy, security and IT-quality requirements into one coherent, risk-based framework, ensuring low-risk internal tools are not governed like regulated clinical systems. Retire SDLC controls that do not reduce risk and ensure tooling is implemented to securely speed up software development at Novartis at the highest scale, leveraging and creating AI tooling for the enterprise. Implement policy as code and controls as code, including branch protections, mandatory review, signed commits, segregation of duties, deployment approvals and immutable audit trails. Build automated, continuous evidence pipelines and define control telemetry including coverage, exceptions, drift, mean time to remediate and control effectiveness, with a focus on agility, automation and speed. Own secure-by-default guardrails in golden pipelines and paved-road platforms, aligning with recognized frameworks including NIST SSDF, ISO/IEC 27001 and IEC 62304 where applicable. Define controls for AI-assisted engineering, including acceptable use of coding assistants, agentic tooling, IP and licence exposure, provenance, attribution and human accountability for review and approval. Define controls for AI-containing products, including model lifecycle, dataset and model documentation, evaluation, drift monitoring, explainability, human oversight and readiness for evolving regulatory requirements. Use AI to reduce compliance burden through automated risk assessment drafting, control mapping, test generation, deviation triage and documentation synthesis, while serving as technical authority for inspections, audits, certifications and SDLC remediation.