Senior AI Analytics Engineer

100 Salesforce, Inc.; Bellevue (WA); On-site; USD 172,500 - 260,100; Full time

Benefits offered by this job

Time‑off programs

Medical insurance

Dental insurance

Vision insurance

Mental health support

Parental leave

Life and disability insurance

401(k)

Employee stock-purchasing program

Job summary

Salesforce seeks an AI Software Engineer to advance analytics agents within Tableau. You will build scalable data-intensive systems, shape user experiences with generative AI, and ensure robust performance across enterprise workloads.

Ideal candidates have 10+ years of enterprise engineering experience, expertise in LLMs, and strong Python/Java skills. Expect full-stack responsibilities, streaming data handling, and modern DevOps practices in a fast-paced environment.

Qualifications

• 10+ years of enterprise engineering experience.
• Proven ability to design resilient, scalable AI-enabled systems.
• Strong Python/Java skills and experience in end-to-end product development.

Responsibilities

• Collaborate with product managers, engineers, and researchers to build AI products and prototypes.
• Iterate on ideas to achieve product-market fit for analytics agents.
• Shape user experiences with generative AI capabilities and context engineering.
• Design scalable agentic systems emphasizing throughput, latency, and I/O.
• Evaluate performance against real customer use cases and ensure robustness.
• Implement logging, tracing, and debugging tools; apply DevOps best practices.

Skills

LLMs & agents

Python

Java

Full-stack

Distributed systems

DevOps

Cloud deployments

Streaming data

Education

Job description

Salesforce seeks an AI Software Engineer to advance analytics agents within Tableau. You will build scalable data-intensive systems, shape user experiences with generative AI, and ensure robust performance across enterprise workloads.

Ideal candidates have 10+ years of enterprise engineering experience, expertise in LLMs, and strong Python/Java skills. Expect full-stack responsibilities, streaming data handling, and modern DevOps practices in a fast-paced environment.