Software Engineering SMTS / LMTS – AI Core

🔥 1 minute ago

🏄 California – Remote

🏄 California – Remote

💵 $207.8k - $285.8k / year

⏰ Full Time

🟡 Mid-level

🟠 Senior

🧑‍💻 Full-stack Engineer

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Salesforce

WebsiteLinkedInAll Job Openings

10,000+ employees

Founded 1999

💼 Consulting

📣 Marketing

☁️ SaaS

Consulting • Marketing • SaaS

Salesforce is a leading cloud-based software company that provides a comprehensive customer relationship management (CRM) platform. The platform connects all company data and teams on an integrated, AI-driven system to improve sales, customer service, and marketing efforts. Salesforce offers scalable solutions for businesses of all sizes, including small and medium enterprises, and provides industry-specific solutions to modernize operations, save time, and reduce costs. Salesforce also offers educational resources through Trailhead and a wide selection of apps on AppExchange to extend its CRM capabilities.

📋 Description

• Design, build, and operate retrieval systems using RAG and hybrid search • Own retrieval initiatives from scoping and design through launch, monitoring, and iteration • Drive technical design for frameworks and platform components used to build production agents • Build multi-agent orchestration, shared primitives for prompts and tools, tracing, and evaluation infrastructure • Diagnose answer quality issues by separating retrieval problems from generation problems • Define and track quality bars and lead improvement efforts • Design ingestion, segmentation, labeling, and retrieval models for documents, knowledge bases, and call transcripts • Build evaluation, observability, rollout, offline evaluation, online monitoring, and regression detection practices • Evaluate solution paths and determine when to trust, redirect, or override model and agent output • Define and track performance and scaling targets for retrieval, indexing, LLM provider usage, and agent orchestration • Ensure reliability and performance of owned systems • Participate in on-call and lead incident resolution • Use coding agents for implementation, testing, refactoring, and documentation • Create reusable workflows, patterns, and tooling to improve team effectiveness • Partner with product, design, and engineering leadership on roadmap, tradeoffs, requirements, and execution plans • Mentor engineers, conduct code reviews, and improve engineering standards, tooling, and processes

🎯 Requirements

• Proven experience shipping production AI or backend systems in a high ownership environment, with a recent focus on LLM-powered applications • Expertise building retrieval systems using RAG and hybrid search, including chunking and indexing strategy, embeddings, vector and lexical search, reranking, and measuring retrieval quality • Expertise building developer tooling for production agents, including potential experience with multi-agent orchestration, agent and tool registries, and shared infrastructure for tracing and evaluation • Experience owning platform initiatives from design through adoption across retrieval and indexing, LLM provider integrations, and agent orchestration • Demonstrated technical leadership on significant projects and non-trivial technical problems • Strong track record delivering complex projects with multiple stakeholders, dependencies, or phases • Strong backend engineering fundamentals • Proficiency in Ruby on Rails, Python, JavaScript, or Go • SQL and RDBMS experience; PostgreSQL preferred • Hands-on experience with the AI application lifecycle, including experiment setup, dataset curation, offline evaluation, error analysis, deployment, and online evaluation • Ability to operate in ambiguity and drive clarity • Strong cross-functional communication skills • Ownership mindset and bias for action • Curiosity, continuous learning, and an agent-forward approach • Nice to have: pgvector or other vector indexes and query performance at scale • Nice to have: content ingestion from third-party systems and lifecycle management • Nice to have: conversation or call transcript processing, including PII and consent constraints • Nice to have: evaluation suites for thoroughness and faithfulness • Nice to have: voice or real-time conversational agents • Nice to have: enterprise SaaS, B2B marketing or sales technology, or Salesforce/CRM integrations • Nice to have: startup experience and rapid shipping

🏖️ Benefits

• Time off programs • Medical insurance • Dental insurance • Vision insurance • Mental health support • Paid parental leave • Life insurance • Disability insurance • 401(k) • Employee stock purchasing program • Potential incentive compensation • Potential equity • Reasonable accommodation during the application or recruiting process