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# Senior Software Engineer

- **Company:** Salesforce Inc.
- **Location:** Palo Alto, CA, United States
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Clean Code Principles, Java (Programming Language), Artificial Intelligence, Amazon Web Services, Amazon S3, Automation of Tests, Cursor, Amazon DynamoDB, JSON, Python (Programming Language), Apache Maven, Microsoft Office, Node.Js, Service Development Studio, TypeScript, GitHub Copilot, Large Language Models, Claude Code, Backend, Agentic-AI, Restful APIs, Docker, Jenkins
- **Published:** November 7, 2026
- **Apply:** https://www.juju.com/job/28_25303_d823dc19ce9d78744bb2dfadc5773e8c

## About the Role

* 4+ years of professional Java development experience.
 * A demonstrated, genuine AI-first approach to engineering, using AI to move faster, build fluency across the stack, and contribute well beyond your core specialty.
 * Experience using AI tools (e.g., Claude Code, GitHub Copilot, Codex, Cursor, etc.) in active development workflows.
 * Ability to design, iterate on, and test system and user prompts that produce structured, parseable LLM outputs (JSON classification, multi-field extraction).
 * Designing and consuming RESTful APIs alongside working knowledge of AWS (S3, STS, KMS, Lambda, DynamoDB).
 * Experience with Bazel or Maven and a strong willingness to work in a monorepo.
 * Experience with Jenkins or equivalent CI/CD pipelines, Docker image creation, and container operations.
 * Experience with TypeScript (Node) and/or Python service development is a strong plus.
 * Office-Flex: work in-person three days per week; or 10 days per quarter for some engineering teams.

## Description

* Build and ship high-quality, production-grade software ,with AI as a core part of your development workflow by pushing the boundaries of AI development tools to deliver secure, optimized, and high-quality code.
 * Design and orchestrate complex systems where AI agents integrate seamlessly into human workflows, driving efficiency and innovation at scale.
 * Architect and maintain resilient backend services integrating Large Language Models (LLMs) via external APIs, while implementing robust observability frameworks (logs, metrics, traces) to monitor long-running AI jobs.
 * Critically evaluate code (Human or AI-generated) for correctness, quality, security, and performance.
 * Develop test automation and quality tooling, focusing on unit/CI test generation, test failure analysis, and flake awareness.