Remote Senior Software Engineer - AI Core & Retrieval

Salesforce, Inc.; San Francisco (CA); Remote; USD 173,000 - 286,000; Full time

Job summary

Salesforce, Inc. is seeking an Engineer for the AI Core team to turn ambiguous AI problems into durable, high‑quality systems. You’ll own retrieval, embedding, and agent infrastructure powering how AI agents access knowledge and ship production agents safely.

You will lead end‑to‑end initiatives around faithful answering, hybrid search, and content lifecycles, collaborating with product, design, and leadership to define what to build and how to measure impact.

Qualifications

• Proven experience shipping production AI or backend systems in a high-ownership environment.
• Expertise building retrieval systems using RAG and hybrid search, with chunking and indexing.
• Experience building developer tooling for production agents and orchestration.
• Ownership mindset and ability to lead platform initiatives from design through adoption.

Responsibilities

• Lead retrieval initiatives end to end: design, build, operate retrieval systems with RAG and hybrid search.
• Develop tooling for production agents: frameworks, multi-agent orchestration, prompts, tools, tracing, evaluation.
• Own answer quality: diagnose weak or inconsistent answers and raise the bar for retrieval quality.
• Design content and data models for ingestion, segmentation, labeling, and retrieval with freshness and dedupe rules.
• Ensure safe ship practices: offline evals, online monitoring, and controlled rollout of prompts and models.
• Set performance targets for retrieval, indexing, and agent orchestration across the platform.

Skills

Production AI

Backend systems

Retrieval systems

RAG

Hybrid search

Developer tooling

Agent orchestration

Ruby on Rails

Python

JavaScript

Go

PostgreSQL

LLM lifecycle

Code review

Tools

pgvector

Job description

Salesforce, Inc. is seeking an Engineer for the AI Core team to turn ambiguous AI problems into durable, high‑quality systems. You’ll own retrieval, embedding, and agent infrastructure powering how AI agents access knowledge and ship production agents safely.

You will lead end‑to‑end initiatives around faithful answering, hybrid search, and content lifecycles, collaborating with product, design, and leadership to define what to build and how to measure impact.