4 часа назад
Senior Fullstack Engineer (AI)
140 000 - 200 000$
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
Текст:
TL;DR
Senior Fullstack Engineer (AI): Building and shipping full-stack features across LeanData’s Salesforce managed package, orchestration systems, and new AI and agent-based products with an accent on TypeScript, Node.js, Salesforce, and scalable service design. Focus on modernizing legacy frontends, designing APIs and service boundaries, debugging production systems, and applying AI tooling throughout the software development lifecycle.
Location: Santa Clara, United States; hybrid work
Compensation: OTE $140,000–$200,000 per year
Company
develops a Salesforce managed package, orchestration systems, and new AI and agent-based products.
What you will do
- Design, build, and ship full-stack features end to end, from specification through deployment.
- Own significant technical initiatives and establish engineering standards and best practices.
- Use AI tooling across specification, development, code review, and testing, while improving team practices.
- Debug and resolve production issues across modern and legacy codebases.
- Design scalable systems, data models, interfaces, service boundaries, REST APIs, and asynchronous services.
- Modernize legacy frontends and develop customer-facing or agent-based AI products.
Requirements
- Senior-level experience building and shipping full-stack web applications to production.
- Strong TypeScript skills and experience with modern JavaScript frameworks.
- Backend experience with Node.js, Express, PostgreSQL, REST APIs, and asynchronous services.
- Experience with scalable system design, cloud-based systems, deployments, CI/CD, and iterative review processes.
- Solid Apex and Salesforce experience, including triggers, SOQL, governor limits, bulkification, and test patterns.
- Salesforce Platform Developer certification and experience with managed packages, Visualforce, or Lightning Web Components.
Culture & Benefits
- Hybrid work environment in Santa Clara.
- Quality, maintainability, reuse, and reducing bugs are treated as first-class engineering outcomes.
- Ownership is expected from ambiguous requirements through production delivery.
- AI adoption is encouraged with pragmatic judgment about its limitations and output quality.
- Technical trade-offs are made explicit and communicated clearly to the team.
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