Principal Engineer - AI ML and Cloud Security

Overview

Hands-on analytical role in GSK's AI Platform and Cloud Security team, supporting AI tool security posture and cloud security advisory across Azure and GCP. The team advises and flags issues; platform teams own remediation.

What you'll do

• Run CSPM analysis across Azure and GCP in Prisma Cloud, Wiz or Upwind, producing findings clear enough for a platform team to act on without a follow-up meeting.
• Maintain the shadow AI register and run the discovery scans that populate it, across sanctioned and unsanctioned AI tooling.
• Apply agent and model risk-tiering to AI deployments and track each assessment through to a governance decision.
• Support LLM and API exposure risk assessments with analysis and evidence, referencing MITRE ATLAS and the OWASP Top 10 for LLM Applications.
• Support cloud IAM and entitlement review packs, including CIEM analysis of over-permissioned identities, and track outcomes to closure.
• Track remediation owned by the Azure and GCP platform teams and business units, and escalate where it stalls.
• Produce KPI data and build Power BI dashboards for cloud and AI security posture, including drift against configuration baselines.
• Improve the team's analysis and reporting through automation in Python.
• Use approved AI tools in your day-to-day work, validating outputs and following GSK's Responsible AI, privacy and security requirements.
• Design and build the automation and tooling that produces the posture, shadow AI and agent risk picture, documenting trade-offs.
• Mentor junior analysts and engineers on cloud and AI posture work, and review their output before it is relied on.
• Apply GxP and data integrity expectations to posture reporting that covers validated systems.

What you'll need

• 10+ years in cloud or platform security in a regulated environment.
• CSPM analysis across Azure and GCP using Prisma Cloud, Wiz or Upwind, with remediation owned by others chased and escalated.
• Maintaining a shadow AI register populated by discovery programmes, classifying AI tools, copilots and LLM APIs by data exposure and risk, and tracking agent risk-tiering to decision.
• Analysing LLM and AI API exposure across Azure and GCP (Azure OpenAI, Vertex AI, model endpoints, keys and network exposure) and supporting cloud IAM review packs.
• Python, SQL or scripting for posture data, producing AI and cloud security KPIs and dashboards with audit-ready accuracy.
• Bachelor's degree in a relevant discipline, or equivalent professional experience.

Nice to have

• Cloud security certification such as CCSP, AZ-500 or Google Professional Cloud Security Engineer.
• AI security posture management (AI-SPM) tooling and LLM API risk assessment.
• Power BI or equivalent dashboarding.
• Cloud IAM and AI/LLM security awareness.
• Clear written findings and stakeholder communication with platform engineering teams.

Details

• Location: Bengaluru, India.