Smts/lmts Full Stack Software Engineer, Tableau Next

Salesforce Salesforce · Enterprise · San Francisco, CA +1

Senior/Lead Software Engineer to shape Agentic and Visualization Experiences for Tableau Next. Drive design and development of high-performance, scalable platforms for analytical experiences. Collaborate with UX, backend engineers, and product teams. Explore and integrate emerging visualization technologies and Generative AI-powered intelligence experiences. Integrate and orchestrate LLMs and AI services using APIs, SDKs, and agent frameworks like OpenAI APIs, LangChain, RAG pipelines, tool calling, and vector databases. Familiarity with AI-assisted development workflows and structured/unstructured data systems including vector databases.

What you'd actually do

  1. Architect and develop core visualization components and frameworks for the next-gen Tableau product, ensuring scalability, performance, and flexibility.
  2. Optimize large-scale data rendering with Canvas, WebGLwhile enhancing interactivity through filtering, animations, and real-time updates for a smooth user experience.
  3. Collaborate with UX designers to implement elegant and intuitive visual representations of complex data.
  4. Work collaboratively to design efficient APIs and data-fetching strategies that optimize visualization performance and responsiveness.
  5. Drive innovation by exploring and integrating emerging visualization technologies, frameworks, and methodologies.

Skills

Required

  • 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, HTTP, 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, MCP, 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

Nice to have

  • 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

What the JD emphasized

  • 6+ years of industry experience building enterprise-grade distributed systems at scale
  • Experience integrating and orchestrating LLMs and AI services using APIs, SDKs, and agent frameworks such as OpenAI APIs, LangChain, MCP, 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
  • Understanding of AI reliability and quality practices including prompt testing, model evaluation, hallucination mitigation, observability, guardrails, and human-in-the-loop workflows
  • Deep experience in JavaScript, especially in rendering frameworks (Canvas, WebGL, SVG)
  • Good understanding of AI application architecture including prompt engineering, context management, retrieval systems, embeddings, memory, evaluation, and latency optimization

Other signals

  • integrating and orchestrating LLMs and AI services
  • agent frameworks
  • RAG pipelines
  • tool calling
  • vector databases
  • AI-assisted development workflows
  • structured and unstructured data systems
  • vector databases
  • semantic indexing
  • knowledge retrieval systems
  • AI reliability and quality practices
  • prompt testing
  • model evaluation
  • hallucination mitigation
  • observability
  • guardrails
  • human-in-the-loop workflows
  • AI application architecture
  • prompt engineering
  • context management
  • retrieval systems
  • embeddings
  • memory
  • evaluation
  • latency optimization