Lead Software Engineer
Tableau · Bellevue, WA · 5 days ago
Engineering$173k–$260k/yrFull-time
About the role
Salesforce is seeking a passionate and highly skilled AI/SW Engineer to join the Analytics Agent team. This team develops the #1 AI-powered analytics agents for helping customers see, understand, and act on data.
Responsibilities
- Collaborate with product managers, fellow engineers, and researchers to build next-generation generative AI products and prototypes to make our customers successful.
- Propose and rapidly iterate on ideas and experiments, as though in a startup environment, to achieve product-market fit for cutting-edge analytics agents.
- 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.
- Evaluate the performance and quality of the agentic solutions you are building against customer use cases.
- Solve challenges with probabilistic software, ensuring defensive error handling, streaming data optimization, caching, and explainability.
- Implement logging, tracing mechanisms, and tools to facilitate debugging, diagnostics, and performance tracking.
- Engage in light DevOps tasks, leveraging infrastructure best practices to deploy and monitor AI-driven systems.
Requirements
- 10+ years of enterprise engineering experience.
- Adaptable and Innovative Mindset: Fearless about learning new technologies and excited to work in a fast-paced, ambiguous environment. Possess a problem-first approach with a careful and principled methodology for building resilient systems.
- Expertise in shaping experiences with LLMs and agents.
- Proficient in Python, Java, or other languages. Experience building full-stack applications with expertise in either backend, frontend, or both. Ability to handle error cases, write asynchronous code, and work effectively with streaming data.
- Strong Programming and Distributed Systems Development Skills.
- Experience with Modern Software Development Practices: Familiar with DevOps principles, infrastructure best practices, and cloud-based deployments. Knowledgeable about queues, message buses, and event-driven architectures.