Job Description

MuleSoft is looking for a Principal Architect to lead the architecture strategy in continuing to build the best-in-class Integration and API platform, with a forward-looking focus on AI-led innovations and deep integration across the Salesforce, Data Cloud and Agentforce ecosystem. Our vision is to empower all knowledge workers to design and build APIs and integrations at lightning speeddeployed seamlessly on our iPaaS, public cloud, and on-premises.

In this role, you will help define the next generation of MuleSofts platform by:

• Driving AI-powered investments across the Integration and API lifecycle, from intelligent design-time assistants and code generation to runtime observability and optimization.

• Enabling seamless integration with Salesforce properties like Agentforce, Data Cloud, Heroku and Tableau, so that users can embed integration, automation, and insights directly into their customer workflows.

You are an experienced technical leader with deep domain knowledge in distributed systems and building Platform-as-a-Service (PaaS) offerings. You bring a strong background in Integration, Automation, and Full Lifecycle API Management, and you thrive when leading globally distributed, highly collaborative teams. We're looking for someone who:

• Has a proven track record of building scalable, secure, and resilient enterprise platforms.

• Can lead the technical vision for integrating AI models and services into developer workflows and system runtimes.

• Has experience aligning platform architecture with larger ecosystem goals - especially in the context of Salesforce Data Cloud, Agentforce, and Tableau.

• Is passionate about working in a high-impact role within a community that values continuous learning, shared ownership, and a bias toward action.

Join us in shaping the future of integration and APIs - powered by AI, connected deeply with the Salesforce platform, and built for developers everywhere.

Primary Responsibilities:

• Lead MuleSoft AI Architecture Strategy: Define, build, and oversee the long-term MuleSoft architecture strategy, with a particular focus on scaling our integration and API platform through AI-led capabilities and deep alignment with the Salesforce ecosystem.

• Cross-Functional Collaboration: Partner with Product, Engineering, and Go-To-Market teams - as well as customers and internal Salesforce stakeholders - to ensure that the architecture strategy directly supports key business objectives and customer success.

• Customer Engagement: Engage with strategic customers and partners to understand their architecture needs and validate MuleSofts roadmap, especially around AI-driven integration, API lifecycle automation, and platform extensibility via Salesforce technologies.

• Internal Enablement & Field Partnership: Collaborate with Support, Sales Engineering, and Customer Success to scale platform understanding, drive adoption, and accelerate success across customer implementations. Help these teams articulate the value of our AI investments and integrations with Agentforce, Data Cloud, and Tableau.

• Best Practices & Governance: Establish and promote platform-wide best practices for AI investments. Drive the creation and maintenance of AI architecture governance frameworks (e.g., architecture review boards, standards, and reference architectures).

• Architectural Alignment & Collaboration: Coordinate architectural decisions to ensure coherence, scalability, and extensibility across our integration platform - especially as we invest in AI-assisted developer experiences, real-time data ingestion to Data Cloud, and native insights via Tableau.

Minimum Requirements:

• Bachelors or Masters in Computer Science or Engineering

• At least fifteen (15) years of experience in platform architecture (SaaS, PaaS), including at least three (3) years of experience applying AI/ML technologies to platform or product architecture.

• Demonstrated familiarity with AI/ML-led architectural patterns, such as generative developer experiences, intelligent routing or observability. Experience embedding AI services into platform design is a plus.

• Demonstrable experience and interest in architecting complex and scalable platforms; expert level knowledge of relevant architecture, design principles and patterns.

• Demonstrable experience delivering cloud-native capabilities; experience with integrations, automations and API management is a significant plus.

• Strong critical thinking, decision-making, and problem-solving abilities. Sharp attention to detail while maintaining a broad strategic vision.

Preferred Requirements:

• Strong understanding of Integrations, Automations, and Full Lifecycle API Management, with experience in applying AI-driven techniques such as intelligent workflow orchestration, adaptive API routing, and generative API design.

• Cloud Infrastructure for Intelligent Platforms: Deep understanding of public and private cloud infrastructure, with the ability to lead teams through complex technical challenges in implementing AI-powered capabilities such as real-time event processing, large-scale data ingestion, and low-latency inference pipelines.

• Modern Cloud-Native and AI-Ready Architecture: Broad working knowledge of state-of-the-art cloud technologies, including IaaS, PaaS, containers, distributed analytics, data center deployments, and AI/ML infrastructurewith the ability to architect platforms that are both cloud-native and optimized for intelligent, data-driven workloads.

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