Lead Software Engineer

Salesforce Salesforce · Enterprise · Bellevue, WA

Salesforce is seeking a Lead Software Engineer to join their Tableau team, focusing on developing AI-powered analytics agents. The role involves building next-generation generative AI products, shaping user experiences with LLMs and agents, designing scalable agentic systems, and evaluating their performance. The position requires strong programming and distributed systems skills, experience with modern software development practices, and expertise in shaping experiences with LLMs and agents.

What you'd actually do

  1. Collaborate with product managers, fellow engineers, and researchers to build next-generation generative AI products and prototypes to make our customers successful.
  2. Propose and rapidly iterate on ideas and experiments, as though in a startup environment, to achieve product-market fit for cutting-edge analytics agents.
  3. Build and shape user experiences using context engineering and generative AI capabilities.
  4. Design and build scalable and performant agentic systems, taking throughput and latency into account, recognizing how and where to apply parallel processing, stream processing, and asynchronous I/O.
  5. Evaluate the performance and quality of the agentic solutions you are building against customer use cases.

Skills

Required

  • Python, Java, or other languages
  • backend, frontend, or both
  • error cases
  • asynchronous code
  • streaming data
  • developing, scaling, and maintaining applications at a production scale
  • DevOps principles
  • infrastructure best practices
  • cloud-based deployments
  • queues, message buses, and event-driven architectures
  • LLMs and agents
  • evaluation of ML model performance

Nice to have

  • multi-modal products
  • context engineering
  • parallel processing
  • stream processing
  • asynchronous I/O
  • probabilistic software
  • defensive error handling
  • caching
  • explainability
  • logging, tracing mechanisms
  • debugging, diagnostics, and performance tracking
  • light DevOps tasks

What the JD emphasized

  • 10+ years of enterprise engineering experience
  • Expertise in shaping experiences with LLMs and agents.
  • Proficient with evaluation of ML model performance.

Other signals

  • building groundbreaking, multi-modal products and tools that transform how people engage with data
  • building scalable, data-intensive systems for analytics
  • pushing the boundaries of what AI agents can achieve