2 months ago
Remote, United StatesSenior
Base Salary
$147k - $167k/yr
Responsibilities
- Apply and advance an AI-native software development lifecycle using Claude, ChatGPT, and other AI chat and coding tools.
- Build and maintain Claude plugins, MCP servers, and related tooling that connect AI capabilities to engineering systems and data.
- Deliver reusable Salesforce platform capabilities using Apex, Lightning Web Components, Salesforce DX, custom metadata, platform events, CPQ patterns, and shared libraries.
- Develop and maintain integrations and services using MuleSoft, DataWeave, REST and SOAP APIs, ETL tools, Python, and other object-oriented languages.
- Design, build, and operate scalable solutions on AWS and other cloud services.
- Build and maintain CI/CD pipelines, automated testing, schema validation, deployment automation, version control, and code coverage practices.
- Conduct architecture, solution design, and code reviews across Apex, LWC, Flow, and CPQ implementations.
- Manage sandbox and production environments, investigate bugs and production issues, support Salesforce releases, and maintain system uptime according to SLAs.
- Mentor engineers on Salesforce development, CPQ configuration, architecture, and engineering best practices.
- Collaborate with Product and cross-functional teams to translate business requirements into scalable platform capabilities and influence the technology roadmap.
Requirements
- 10+ years of professional software engineering experience, including at least five years focused on Salesforce in complex, multi-cloud enterprise environments.
- Advanced programming skills in Apex and SOQL/SOSL, with competence in Lightning Web Components, HTML, JavaScript, and CSS.
- Proficiency in Python or another object-oriented programming language, modern software design, and architecture.
- Experience with MuleSoft Integration Platform, DataWeave, AWS, cloud development, REST APIs, and SOAP APIs.
- Fluency with AI chat and coding tools, experience building Claude plugins or comparable extensions, and experience utilizing and supporting MCP servers.
- Ongoing knowledge of the AI market and a track record of bringing effective AI tools into engineering workflows.
- Experience working on traditional engineering teams in close partnership with Product, including enterprise integrations and distributed systems.
- Experience with DevOps and CI/CD pipelines using GitHub and Gearset.
- Salesforce Administrator and Salesforce Developer or Platform Developer certifications.
- Strong analytical, design, problem-solving, business-requirements documentation, communication, and cross-functional collaboration skills.
- Experience with container-based and serverless architectures, including Docker, Kubernetes, and related orchestration tools.
- Experience with Go, Ruby, JavaScript or Vue.js, Node.js, AWS Lambda, ECS, Fargate, and CodePipeline is an additional qualification.
- Salesforce Platform Developer II certification, Salesforce CPQ and Billing, and Salesforce Experience Cloud experience are additional qualifications.
- Working knowledge of additional languages such as C#, Java, Go, and Ruby is an additional qualification.
- Bachelor’s degree in Computer Science, Business, or Information Systems.
Tech Stack
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