Global Platform Engineer – Sales CPQ PRO AMP

The MedTech commercial transformation is bringing Sales, Marketing, CPQ, PR&O, Customer Service, and Service & Repair capabilities into a connected, AI-enabled customer engagement ecosystem built primarily on Microsoft Dynamics and Microsoft cloud technologies. This role has direct technical accountability for the Sales, CPQ, and PR&O platform domains and will establish patterns that enable interoperability with adjacent CXM capabilities and the broader J&J technology ecosystem.

This person will be the senior technical counterpart to product and business leadership. They will translate product strategy and business priorities into an executable platform architecture, establish engineering standards across delivery teams and partners, and ensure that each release strengthens a durable global platform rather than creating isolated solutions.

Key Accountabilities

1. Platform architecture and technical roadmap: Define and evolve the target architecture and multi-year technical roadmap for the Butterfly CXM platform, with direct accountability for Sales, CPQ, and PR&O. Establish clear platform boundaries, extension patterns, data flows, integration contracts, identity and access patterns, and non-functional requirements. Ensure architecture decisions support global scale, security, privacy, regulatory requirements, reliability, performance, maintainability, and controlled regional variation. Make pragmatic technology trade-offs that balance immediate release needs with the long-term health of the platform.

2. Reusable platform capabilities and developer experience: Define and lead the development of reusable APIs, services, integration patterns, frameworks, SDKs, components, and developer tooling used across CxM product pods. Establish governed patterns for Microsoft Dynamics configuration, customization, integration, data access, testing, release management, and environment management. Create and maintain a catalog of approved platform services, reusable business capabilities, technical patterns, and implementation guidance. Improve developer productivity and delivery quality through automation, standardization, observability, and modern software engineering practices.

3. AI and agent engineering: Define the technical approach for embedding AI and agent-based capabilities into priority commercial workflows across Sales, CPQ, and PR&O. Lead reusable patterns for agent orchestration, tool calling, skills, context management, retrieval-augmented generation, human oversight, evaluation, and lifecycle management. Partner with enterprise AI platform teams to implement governed execution, security controls, observability, discoverability, and production operations. Advance interoperability patterns, including Model Context Protocol and agent-to-agent integration, where they are appropriate, approved, and valuable.

4. Engineering governance and delivery leadership: Own CXM platform engineering standards and technical guardrails while aligning with enterprise architecture, cloud, cyber security, privacy, data, and AI policies. Provide technical direction and quality oversight across internal engineers, product pods, contractors, systems integrators, and strategic technology partners. Lead architecture reviews, resolve cross-team technical dependencies, and intervene early when delivery choices create platform risk or unnecessary duplication. Coach engineers and technical leads, strengthen engineering capability, and create a culture of accountability, reuse, documentation, and continuous improvement. Communicate architecture decisions, risks, trade-offs, and investment needs clearly to product, business, technology, and executive stakeholders.

Measures of Success

• A clear target architecture and sequenced engineering roadmap are established and used to guide investment and delivery decisions.
• Product pods adopt common engineering standards, integration contracts, and reusable platform capabilities.
• Duplicated solutions and one-off regional implementations are reduced in favor of governed reuse and configuration.
• Platform reliability, security, release quality, developer productivity, and time to deliver improve through measurable engineering practices.
• Priority AI capabilities progress from demonstrations to secure, observable, supportable production services with defined business outcomes.
• Technical decisions are made at the right level without requiring product leadership to mediate routine architecture and engineering issues.