Software Engineering - Core Software Engineering - Software Engineering PMTS-2

Salesforce•San Francisco, CA

12h

About The Position

Salesforce is seeking an exceptional Principal Member of Technical Staff to lead the engineering vision for AgentExchange's Search and Personalization services. This role is crucial for the AI-powered discovery layer that enables customers to find and engage with solutions across the Salesforce ecosystem. The Principal Engineer will be the technical authority for systems that influence customer visibility, searchability, and interaction with AgentExchange. The position involves designing and delivering the next generation of agentic search, including multi-turn, context-aware search enriched with AI overviews, next-best query suggestions, and personalized recommendations. This also includes the indexing infrastructure and contextual discovery services powering various Salesforce surfaces. AgentExchange is evolving into a next-generation ecosystem marketplace, integrating Agentforce, MuleSoft, Tableau, and Slack, with full transactability from discovery to purchase and provisioning. The One AppExchange Framework provides a dynamic, extensible data and services platform. This is a leadership role focused on owning the technical vision for discovery at scale, driving AI-native engineering, and setting standards for relevance, latency, personalization, and observability.

Requirements

10+ years of experience in software engineering, with a demonstrated track record of technical leadership on enterprise-scale search, recommendation, or personalization systems.
Proven ability to define and drive long-term technical vision and architectural roadmaps for large, complex search or ML-infused platform domains.
Deep expertise in building and operating search systems at scale, including search engine internals (indexing pipelines, ranking, query understanding, relevance tuning) and search infrastructure (Elasticsearch, OpenSearch, Solr, or equivalent).
Backend experience with Node.js, Java, or equivalent for high-throughput search services.
Experience designing and delivering recommendation or personalization systems (collaborative filtering, content-based ranking, behavioral signal processing, or equivalent).
Hands-on experience integrating LLMs or GenAI into search products (AI-generated summaries, query expansion, semantic search, or conversational retrieval).
Experience with real-time and near-real-time data pipelines for indexing and signal ingestion.
Strong commitment to engineering excellence: observability, telemetry, latency SLOs, CI/CD, service ownership, safe change practices, and production reliability.
Excellent communication skills, able to influence and build consensus across engineering, product, and executive stakeholders.
Proficient in written and spoken English.

Nice To Haves

Experience building multi-turn or conversational search experiences, including context management and session-aware ranking.
Hands-on experience with agentic systems, MCP tools/resources, or A2A patterns, particularly catalog and metadata requirements for new AI-native asset types.
Experience with contextual or embedded discovery surfaces, delivering search within host product surfaces (e.g., in-app, in-builder, in-Slack contexts).
Familiarity with marketplace or e-commerce search (faceted navigation, intent classification, CTR optimization, and funnel instrumentation).
Experience with personalization at scale (user modeling, preference inference, A/B experimentation, and behavioral analytics).
Experience with platform infrastructure migrations (e.g., Heroku → cloud-native platforms) and tech stack modernization.
Strong security mindset, including experience with data governance, access control, and security best practices for search and recommendation systems.
Conversant with Salesforce Platform features and best practices.
A strong desire to learn technology and a polyglot attitude.

Responsibilities

Lead architectural design and delivery of major Search & Personalization capabilities, including GenAI search (AI overview results, next-best query suggestions, natural language query understanding), multi-turn agentic search (conversational discovery with recommendations, comparisons, and contextual follow-up), personalization service (behavioral and preference-based ranking and recommendations), contextual discovery service (powering embedded AgentExchange discovery surfaces), and search indexer (scalable, low-latency indexing pipelines for new asset types).
Champion AI-native engineering by actively using and promoting AI tools across the development lifecycle, from code completion to production monitoring, and fostering an AI-native team culture.
Define the Northstar architecture for the Search & Personalization domain, leading discovery, design, and execution tracks aligned with the broader AgentExchange one-marketplace strategy.
Drive platform modernization, contributing to the migration off Heroku and onto Falcon, including the enabling roadmap for search services infrastructure migration.
Own engineering excellence across the search stack, focusing on observability and telemetry (SLOs/SLIs, latency budgets, relevance metrics), safe change practices, 99.95% availability targets, and security risk governance.
Act as the technical authority for the domain, providing guidance, mentorship, and sponsorship to engineers, and fostering a culture of technical excellence and bold innovation.
Collaborate cross-functionally with Product, Platform Services, Marketing and Growth, and Embedded Exchanges teams to deliver shared discovery infrastructure, unified catalog indexing, and contextual search surfaces across all AgentExchange touchpoints.
Be a culture carrier, embodying Salesforce values (Trust, Innovation, Engineering Commitment, Curiosity), challenging the status quo, and building the best-engineered solutions.