Software Engineering LMTS

Salesforce•Bellevue, WA

4d•$172,500 - $260,100

About The Position

Salesforce is seeking a passionate and highly skilled AI/SW Engineer to join our team in Tableau developing the #1 AI-powered analytics agents for helping customers see, understand, and act on data. On the Analytics Agent team, you will work at the forefront of agentic application development, building groundbreaking, multi-modal products and tools that transform how people engage with data. This is an opportunity to contribute to a dynamic, fast-paced environment, applying your expertise to build scalable, data-intensive systems for analytics. We're looking for curious and motivated engineers who want to play a significant role in pushing the boundaries of what AI agents can achieve.

Requirements

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 with evaluation of ML model performance.
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.
Professional experience in developing, scaling, and maintaining applications at a production scale.
Familiar with DevOps principles, infrastructure best practices, and cloud-based deployments.
Knowledgeable about queues, message buses, and event-driven architectures.

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.
Build and shape user experiences using context engineering and generative AI capabilities.
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.