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, 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.
• Work collaboratively to 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.
• Expertise in database technologies including SQL, PL/SQL, relational schema design, and implementing web services and RESTful APIs.
• Proficiency 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.
• 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.
• Experience working with structured and unstructured data systems including SQL/NoSQL databases, vector databases, semantic indexing, and knowledge retrieval systems.
• Experience architecting, developing, and deploying 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.
• Experience building developer-facing AI tooling or internal AI platforms.
• Experience with data visualization tools like Tableau or similar BI platforms, and a basic understanding of VizQL concepts.
• 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.