Software Engineering SMTS / LMTS – AI Core

🕒 il y a 15 jours

🏄 California – Distant

🏄 California – Remote

💵 $207 800 - $285 800 / an

⏰ Temps Plein

🟡 Intermédiaire

🟠 Senior

🧑‍💻 Développeur Full-Stack

🦅 Parrain de Visa H1B

Cette entreprise a parrainé des visas H1B par le passé.

👻 Score fantôme 0%

Ce que ça veut dire : la probabilité que personne ne recrute vraiment pour cette offre.Comment le lire : 60 % ou plus, on pense que c'est une offre fantôme. Un score plus bas est moins inquiétant.Comment on la calcule : ancienneté, republications, postes ouverts vs taille de l'équipe, rapidité de clôture, et si le salaire est indiqué.À noter : une estimation à partir de données publiques, pas un jugement sur l'entreprise. De vraies offres peuvent avoir un score élevé, alors prenez-le comme un indice, pas comme un fait.

Postuler Maintenant

Trouver des Emplois à Distance Similaires

Salesforce

Site WebLinkedInTous les Emplois

10 000+ employés

Fondée en 1999

💼 Conseil

📣 Marketing

☁️ SaaS

Consulting • Marketing • SaaS

Salesforce est la plateforme de gestion de la relation client (CRM) la plus fiable au monde, conçue pour réunir les équipes marketing, commerciales, de commerce, de service et IT afin d'améliorer les relations avec les clients. Elle propose des solutions telles que Sales Cloud pour conclure des affaires, Service Cloud pour le support clients, et Marketing Cloud pour bâtir des relations clients durables. Salesforce encourage la croissance des entreprises de toutes tailles avec sa plateforme complète, dotée d'agents d'IA autonomes et de données unifiées. L'entreprise soutient l'apprentissage grâce à son programme Trailhead, qui offre des parcours guidés pour développer des compétences sur Salesforce, numériques et relationnelles. Plus de 150 000 entreprises font confiance à Salesforce, qui se distingue non seulement par sa technologie, mais aussi par son engagement à créer de meilleures pratiques d'affaires et des communautés.

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

🎯 Exigences

• 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

🏖️ Avantages

• 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

📊 Vérifiez votre score de CV pour ce poste

Améliorez vos chances d'obtenir un entretien en vérifiant votre score de CV avant de postuler.

Télécharger le CV