Sr. Full-Stack Developer - AI-forward

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.