Software Engineering LMTS

Salesforce

Remote

Quick summary

Work type: Remote
Location: Remote
Salary: $172,500–$260,100 / yr
Posted: 5 days ago

Market check

Salary context

Above market

How this pay compares to similar roles

Similar $170k

This role $216k

$123k most similar roles pay here $275k

This role pays more than 82% of similar roles. Most pay $137,500–$203,475 — the shaded band above. At the midpoint, this role pays about $216k versus about $170k for comparable roles.

Based on 240 similar postings.

Employer

About Salesforce

Salesforce is the world''s leading customer relationship management (CRM) platform, offering cloud-based software for sales, service, marketing, analytics, and application development. Industry: Enterprise Software & Cloud Computing

Salesforce currently has 132 open roles on FindRole.

Listed pay typically runs $171,200–$260,100 across 116 roles with salary data.

Most-posted roles

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At a glance

TL;DR · Software Engineering LMTS

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Join Salesforce’s Tableau team as an AI/SW Engineer and contribute to the development of cutting-edge analytics agents, transforming how customers interact with data. You will collaborate closely with product managers and researchers to build innovative generative AI products, iterating rapidly on ideas to achieve market fit. Your responsibilities include designing scalable agentic systems, evaluating performance against real-world use cases, and implementing robust logging and tracing mechanisms for debugging and diagnostics. This role requires expertise in LLMs and agents, proficiency in Python or Java, and experience with distributed systems development and modern software practices such as DevOps and cloud-based deployments. Ideal candidates are adaptable, innovative, and excited to work in a fast-paced environment where they can push the boundaries of AI-driven analytics solutions.

Skills

Python Java DevOps Docker Kubernetes AWS CI/CD PostgreSQL Redis RabbitMQ Prometheus Grafana Git Jenkins Terraform GraphQL React Node.js MongoDB

What you'll do

Propose and iterate on AI product ideas to achieve market fit.
Build scalable agentic systems considering throughput and latency.
Evaluate agentic solutions against real customer use cases.
Implement logging, tracing mechanisms for debugging and performance tracking.
Solve challenges with probabilistic software and ensure explainability.
Engage in DevOps tasks for deploying and monitoring AI-driven systems.
Design user experiences using context engineering and generative AI capabilities.

What we're looking for

Experience in developing full-stack applications with proficiency in Python or Java.
Expertise in building and scaling distributed systems at production scale.
Strong skills in evaluating machine learning model performance.
Proficiency in modern software development practices, including DevOps principles.
Knowledge of cloud-based deployments and event-driven architectures.
Ability to design user experiences using context engineering and generative AI capabilities.

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