Director, Global Customer Platforms Engineering

Job Title:
Director, Global Customer Platforms Engineering

GCL : F

Introduction to role:

Are you ready to harness responsible AI and modern engineering to elevate global customer platforms that directly improve patient and caregiver experiences? You will be responsible for the engineering strategy behind our enterprise-scale platforms in this role. You will apply healthcare, pharmaceutical-focused, customer engagement, and data analytics cloud solutions. This will build measurable business results and real impact for those living with rare and devastating diseases.

Here, you will compose how we build, release, and evolve capabilities guided by live signals and real-world performance. You will set the standards, controls, and guardrails that ensure security, privacy, accessibility, and reliability, so our teams can adapt quickly with confidence and our patients benefit. Can you envision leading a high-performing team to turn telemetry into rapid improvement and shift incidents into automation designed to avoid their recurrence?

AI-Enabled Platform Delivery:
Build and deliver AI-enabled capabilities across healthcare-focused clouds, life sciences-specific cloud environments, customer experience platforms, and analytics, ensuring solutions meet defined business outcomes and user performance targets.

Iterative Releases and Live Optimization:
Use short delivery cycles and incremental releases to improve solutions based on live signals (support tickets, telemetry, user feedback), prioritizing changes that increase patient and customer value.

End-to-End Engineering Ownership:
Lead the engineering lifecycle from development initiation through environment strategy, branching/versioning, CI/CD pipelines, and release validation; make delivery repeatable, audit-ready, and resilient.

Standards, Security and Quality Gates:
Set and uphold engineering standards and quality gates for security, privacy, accessibility, and performance inside pipelines; drive practical test automation (unit, integration, end-to-end) and performance checks that protect users and accelerate delivery.

AI-Assisted SDLC Enablement:
Operationalize AI-assisted workflows across discovery, design, build, test, release, and maintenance with defined guardrails and evaluation metrics; improve developer experience and release pace without compromising safety.

Responsible AI Rules:
Define clear rules for responsible AI use—data handling, model and prompt usage, safety checks, and traceability of AI-generated assets—suitable for audits and regulated contexts.

Embedded AI Controls:
Embed AI controls in delivery and runtime, including pre-release checks, protection of critical data, and safe use of Einstein and generative features to ensure credible outcomes.

Shared Services and Tooling Partnerships:
Partner with collaborators to evolve shared services (identity, consent, data model governance via Data Cloud/MDM), integration accelerators, and developer experience tooling that shorten time-to-value across teams.

Service Readiness and Reliability:
Work with Service Delivery Managers to provide technical readiness gates, risk assessments, and stability plans; convert incident and problem findings into standards, fixes, and automation in the backlog to drive long-term reliability.

• 12+ years in software/product engineering with 5+ years leading Salesforce-centric platforms (Health Cloud, Life Sciences Cloud, Experience Cloud, Marketing Cloud, Analytics); healthcare or pharmaceutical experience strongly preferred.
• Validated application of AI in the Salesforce SDLC (code generation, test automation, documentation synthesis, incident triage) with measurable cycle-time and quality improvements; familiarity with responsible AI practices.
• Hands-on with Apex, Lightning Web Components, Flows, SOQL, platform events; integration via Mule Soft/APIs; CI/CD with development coordinated through version control; observability via Event Monitoring/Health Check; performance tuning and governor-limit management.
• Strong grasp of secure development (OAuth/JWT, field-level security, Shield encryption), privacy-by-design (consent, data…