Software Engineering SMTS / LMTS – AI Core

🕒 Outubro 15

🏄 California – Remoto

🏄 California – Remote

💵 $207.800 - $285.800 / ano

⏰ Tempo Integral

🟡 Pleno

🟠 Sênior

🧑‍💻 Engenheiro Full-stack

🦅 Patrocina Visto H1B

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Salesforce

SiteLinkedInTodas as Vagas

10.000+ funcionários

Fundada em 1999

💼 Consultoria

📣 Marketing

☁️ SaaS

Consulting • Marketing • SaaS

O Salesforce é uma empresa líder em software baseado em nuvem que fornece uma plataforma abrangente de gerenciamento de relacionamento com o cliente (CRM). A plataforma conecta todos os dados e equipes da empresa em um sistema integrado e orientado por IA para melhorar as vendas, o atendimento ao cliente e os esforços de marketing. O Salesforce oferece soluções escaláveis para empresas de todos os portes, incluindo pequenas e médias empresas, e fornece soluções específicas para setores industriais que modernizam operações, economizam tempo e reduzem custos. O Salesforce também oferece recursos educacionais através do Trailhead e uma ampla seleção de aplicativos no AppExchange para expandir as capacidades de seu CRM.

Descrição

• 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

🎯 Requisitos

• 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

🏖️ Benefícios

• 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

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