Principal Software Engineer (Backend, Connectivity)

Join our growing engineering team as a Principal Software Engineer (Backend, Connectivity). In this role, you will lead the design and development of core integration capabilities and scalable connectivity solutions across MuleSoft, Salesforce, and Agentforce. You will collaborate with cross-functional teams, set technical direction, drive innovation, and provide technical leadership and mentorship to engineering teams. This position offers a comprehensive benefits package, including medical care, life insurance, retirement savings, and paid time off.

• Lead the design and development of core integration capabilities and scalable connectivity solutions across MuleSoft, Salesforce, and Agentforce.
• Collaborate with cross-functional teams to define requirements and translate them into technical solutions, setting technical direction and shaping long-term strategy.
• Provide technical leadership and mentorship to engineering teams, promoting best practices in coding, design, and architecture.
• Strong troubleshooting skills with the ability to triage complex issues and identify opportunities to improve product quality and reliability
• 8+ years of experience building and operating production-grade software systems
• Hands-on experience designing and building APIs, asynchronous workflows, and event-driven systems
• Ability to think holistically about architecture, performance, and operational stability
• Ability to communicate complex ideas clearly and work effectively with engineers, designers, and product teams
• Strong proficiency in Java and Spring Boot, or in comparable languages and frameworks for building scalable backend systems
• Experience working with large codebases and influencing design decisions across teams
• Hands-on experience with MuleSoft platform (Anypoint Studio, Mule Runtime, Anypoint Connectors)
• Expertise in Salesforce platform, including Apex, Lightning Components, and Salesforce APIs
• Solid experience with system performance tuning, memory management, and optimizing resource usage in distributed environments
• Familiarity with container runtimes such as Docker and orchestration tools like Kubernetes
• Familiarity with large language models (LLMs), RAG architecture, and integration of AI into developer workflows