Software Engineering SMTS / LMTS - AI Core (REMOTE)
$173k - $260k • Remote • California - San Francisco
Posted 6d ago
Job Location
California - San Francisco
Tech Stack
Remote Work Policy
Fully remote
Categories
AI Agent Engineer
About the job
Salesforce is seeking a technical leader for its AI Core team to build durable, high-quality systems that address complex AI challenges. This role involves developing retrieval systems and agent infrastructure, enabling AI agents to effectively find, trust, and utilize knowledge. You will also create developer tooling to help engineers across the company rapidly and safely deploy production agents. The position offers end-to-end ownership, from scoping and implementation to deployment and iterative improvement, within a high-ownership, high-velocity environment focused on AI and product development.
Responsibilities
- Lead end-to-end retrieval initiatives, designing, building, and operating systems using RAG and hybrid search.
- Own the delivery of retrieval systems from scope and design through launch, monitoring, and iteration.
- Build developer tooling for production agents, including frameworks for multi-agent orchestration and shared primitives for prompts, tools, and tracing.
- Diagnose and improve answer quality by separating retrieval problems from generation problems.
- Design content and data models for ingesting, segmenting, labeling, and retrieving content.
- Ensure AI changes are safe to ship by building evaluation, observability, and rollout practices.
- Set and track performance and scaling benchmarks for retrieval, indexing, LLM provider usage, and agent orchestration.
- Own the operational health of systems, ensuring reliability and performance, and participating in on-call rotations.
- Utilize agentic development for implementation, testing, refactoring, and documentation.
- Create reusable workflows, patterns, and tooling to enhance team effectiveness.
- Partner with product, design, and engineering leadership to shape roadmaps and strategy.
- Mentor engineers, provide code reviews, and improve team standards, tooling, and processes.
Requirements
- Proven experience shipping production AI or backend systems in a high-ownership environment.
- Recent focus on LLM-powered applications.
- Expertise in building retrieval systems using RAG and hybrid search, including chunking, indexing, embeddings, vector/lexical search, reranking, and quality measurement.
- Expertise in building developer tooling for production agents, potentially including multi-agent orchestration frameworks and agent/tool registries.