SMTS/LMTS Full Stack Software Engineer, Tableau Next

Responsibilities Architect and develop core visualization components and frameworks for the next‑gen Tableau product, ensuring scalability, performance, and flexibility. Optimize large‑scale data rendering with Canvas and WebGL while enhancing interactivity through filtering, animations, and real‑time updates for a smooth user experience. Collaborate with UX designers to implement elegant and intuitive visual representations of complex data. Design efficient APIs and data‑fetching strategies that optimize visualization performance and responsiveness. Drive innovation by exploring and integrating emerging visualization technologies, frameworks, and methodologies. Improve code quality and maintainability through best practices, including modularization, automated testing, and continuous integration. Mentor and guide junior engineers, fostering a culture of technical excellence and innovation. Identify and address performance bottlenecks, ensuring smooth rendering and interactions across different platforms and devices. Qualifications 6+ years of industry experience building enterprise‑grade distributed systems at scale. Strong computer science foundation including data structures, algorithms, and design patterns, with a proven track record in software architecture and system design. Experience with object‑oriented programming languages such as Java and JavaScript. Experience with database technologies including SQL, PL/SQL, relational schema design, and implementing web services and RESTful APIs. Expertise in modern web technologies and frameworks including Node.js, React, HTML5, CSS/SASS, JSON, and Web Components standards (Shadow DOM, Custom Elements, etc.). Proficiency in web technologies and real‑time interaction patterns including streaming APIs, WebSockets, and event‑driven architectures. Proficiency in engineering best practices including fault tolerance, concurrency, reusability, extensibility, API design, database modeling, maintainability, security, scalability, testability, and overall software quality. Experience integrating and orchestrating LLMs and AI services using APIs, SDKs, and agent frameworks such as OpenAI APIs, LangChain, RAG pipelines, tool calling, and vector databases. Familiarity with AI‑assisted development workflows including code generation tools, automation agents, and developer productivity tooling. Experience working with structured and unstructured data systems including SQL/NoSQL databases, vector databases, semantic indexing, and knowledge retrieval systems. Architect, develop, and deploy enterprise‑scale product features powered by LLMs, prioritizing an AI‑first methodology that minimizes manual coding. Collaborate closely with Product Management on transforming high‑level business goals into machine‑actionable specs that define non‑goals, user journeys and technical constraints. Prompt engineering at scale – understands that prompts are code: versioned, tested, and monitored. Conduct technical design reviews, establish LLM coding patterns for the team, and mentor engineers on GenAI best practices. Experience building developer‑facing AI tooling or internal AI platforms. Stay current on the rapidly evolving LLM ecosystem and bring relevant techniques, tools, and models to the team’s attention. Bonus Qualifications Familiarity with data visualization tools like Tableau or similar BI platforms, and a basic understanding of VizQL concepts. Strong understanding and hands‑on experience with modern Data Lakes and Data Warehousing providers, such as Snowflake, Databricks, and Salesforce Data Cloud, among others. Deep experience in JavaScript, especially in rendering frameworks (Canvas, WebGL, SVG). Understanding of AI reliability and quality practices including prompt testing, model evaluation, hallucination mitigation, observability, guardrails, and human‑in‑the‑loop workflows. Good understanding of AI application architecture including prompt engineering, context management, retrieval systems, embeddings, memory, evaluation, and latency optimization. Benefits In the United States, compensation offered will be determined by factors such as location, job level, job‑related knowledge, skills, and experience. Certain roles may be eligible for incentive compensation, equity, and benefits. Salesforce offers a variety of benefits to help you live well including: time off programs, medical, dental, vision, mental health support, paid parental leave, life and disability insurance, 401(k), and an employee stock purchasing program. The typical base salary range for this position is $148,500 – $260,100 annually. In select cities within the San Francisco and New York City metropolitan area, the base salary range is $178,900 – $285,800 annually. Accommodations To support a fair recruiting process, we offer reasonable accommodations throughout the hiring process. If you need an accommodation, please submit a request through the Accommodations Request Form. Posting Statement Salesforce is an equal‑opportunity employer and maintains a policy of non‑discrimination with all employees and applicants for employment. We evaluate candidates on the basis of merit, competence, and qualifications – without regard to race, religion, color, national origin, sex, sexual orientation, gender expression or identity, transgender status, age, disability, veteran or marital status, political viewpoint, or other protected classifications. Recruiting, hiring, and promotion decisions are fair and based on merit. The same goes for compensation, benefits, and promotions. #J-18808-Ljbffr Tableau