Essential Functions

AI-SDLC & Engineering Tooling

• Apply and advance our AI-SDLC methodology, using AI chat and coding tools as a core part of the development lifecycle — including Claude, ChatGPT, and open-source alternatives.
• Build and maintain Claude plugins and related tooling that extend AI capabilities into the team’s engineering workflows.
• Build, integrate, and support MCP (Model Context Protocol) servers that connect AI tooling to the team’s systems and data.
• Stay invested in and current with the AI market landscape, continuously evaluating new and best-in-class tools and identifying practical ways to implement them in the team’s day-to-day work.
• Establish patterns and guardrails for safe, effective, and consistent AI-assisted development across the team.

Platform Engineering & Reusable Capabilities

• Deliver reusable platform capabilities such as unlocked packages, shared Apex and LWC libraries, custom metadata frameworks, and CPQ configuration patterns that reduce duplication, enforce consistency, and accelerate team velocity.
• Design scalable solutions using Salesforce DX, platform events, custom metadata types, and cloud-specific best practices, creating the “paved path” that domain teams follow to build reliable, governed features.
• Write production-quality Apex, Lightning Web Components, and integration code. You are expected to contribute directly to the most complex and high-stakes engineering work, not just review it.
• Develop and maintain integration systems and tooling outside of Salesforce, including REST and SOAP APIs, MuleSoft, and ETL tools.
• Build services and automation in Python or another object-oriented language where it is the right tool for the job.

Architecture, Code Quality & Delivery

• Conduct architecture reviews, solution design sessions, and code reviews for complex implementations across Apex, LWC, Flow, and CPQ, identifying opportunities for shared patterns and platform libraries.
• Apply general software engineering and cloud development best practices, designing, building, and operating solutions on AWS and other cloud services.
• Build and maintain CI/CD pipelines using Salesforce DX, Gearset, GitHub, and other industry-standard tools, implementing automated testing strategies, schema validation, and deployment automation that reduce friction and enable safe, frequent releases.
• Conduct and participate in code reviews in GitHub, providing and receiving constructive feedback to continuously raise the quality bar.
• Manage and support sandbox and production environments across the enterprise to ensure successful development, testing, and deployment of new features and functionality.
• Maintain version control and branch hygiene, and ensure code coverage through unit testing.
• Investigate and resolve bugs and production issues autonomously.
• Keep abreast of Salesforce releases and effectively leverage relevant updates; support all releases and maintain system uptime in accordance with SLAs.
• Log and track work in a structured ticketing system (Jira).

Leadership, Mentorship & Collaboration

• Mentor and coach engineers across teams on Salesforce development, CPQ configuration, architectural patterns, and engineering best practices, raising the technical bar organization-wide.
• Collaborate cross-functionally with teams across the entire organization to translate business requirements into scalable platform capabilities.
• Influence the technology roadmap by identifying strategic technical investments, managing technical debt, and aligning platform capabilities with business growth objectives.
• Establish yourself as a primary point of contact for your area of expertise, actively seeking clarification when necessary.

Education and Experience

• 10+ years of professional software engineering experience, with at least 5 years focused on the Salesforce platform in complex, multi-cloud enterprise environments.
• Advanced programming skills in Apex and SOQL/SOSL.
• Competence in Lightning Web Components, HTML, JavaScript, and CSS.
• Proficiency in Python or another object-oriented programming language.
• Experience with the MuleSoft Integration Platform and DataWeave.
• Experience with AWS and cloud development.
• Demonstrated fluency with AI chat and coding tools (e.g., Claude, ChatGPT, and open-source alternatives) as part of an AI-first development workflow.
• Experience building and maintaining Claude plugins (or comparable AI tooling/extensions).
• Experience utilizing and supporting MCP servers.
• A genuine, ongoing investment in the AI market landscape — staying current on new and best-in-class tools and a track record of bringing them into team workflows.
• Experience working on a traditional engineering team in close partnership with Product.
• Proficiency in REST and SOAP APIs.
• Proficiency in modern software design and architecture.
• Salesforce Administrator and Salesforce Developer / Platform Developer certifications.
• Experience with DevOps and CI/CD pipelines — GitHub and Gearset.
• Strong analytical, design, and problem-solving skills.
• Ability to gather and document business requirements effectively.
• Outstanding verbal and written communication skills, with the ability to collaborate effectively within cross-functional teams.

Additional Eligibility Qualifications

• Experience with distributed systems and enterprise-level integrations.
• Experience with container-based and serverless architectures, including Docker, Kubernetes, and related orchestration tools.
• Experience with general-purpose languages and frameworks beyond the Salesforce ecosystem (Go, Ruby, JavaScript/Vue.js, Node.js) and cloud-native development on AWS (Lambda, ECS, Fargate, CodePipeline).
• Salesforce Platform Developer II certification.
• Experience with Salesforce CPQ and Billing.
• Experience implementing Salesforce Experience Cloud.
• Working knowledge of additional high-level programming languages (C#, Java, Go, Ruby, etc.).
• Bachelor’s degree in Computer Science, Business, or Information Systems.