Software Engineering PMTS - Search & Personalization

To get the best candidate experience, please consider applying for a maximum of 3 roles within 12 months to ensure you are not duplicating efforts. Job Category Software Engineering Job Details About Salesforce Salesforce is the #1 AI CRM, where humans with agents drive customer success together. Here, ambition meets action. Tech meets trust. And innovation isn’t a buzzword — it’s a way of life. The world of work as we know it is changing and we're looking for Trailblazers who are passionate about bettering business and the world through AI, driving innovation, and keeping Salesforce's core values at the heart of it all. Ready to level-up your career at the company leading workforce transformation in the agentic era? You’re in the right place! Agentforce is the future of AI, and you are the future of Salesforce. The AgentExchange Search & Personalization team is responsible for the discovery engine that connects customers with the right agents, apps, and integrations at the right moment.. Our goal is to increase the click-through rate to listing detail page views by delivering faster, smarter, and more contextually relevant search and recommendations. We are transforming search from keyword matching into a multi-turn agentic discovery experience powered by GenAI, personalization signals, and real-time behavioral data. We are looking for an exceptional Principal Member of Technical Staff to lead the engineering vision for AgentExchange's Search and Personalization services — the AI-powered discovery layer that sits at the heart of how customers find and engage with solutions across the Salesforce ecosystem. As a Principal Engineer on the Search & Personalization team, you will be the technical authority for the systems that determine what customers see, find, and click on across AgentExchange. You'll design and deliver the next generation of agentic search — multi-turn, context-aware, and enriched with AI overviews, next-best query suggestions, and personalized recommendations — alongside the indexing infrastructure and contextual discovery services that power embedded surfaces across Agentforce, Slack, Setup, and beyond. AgentExchange is building the next generation of our ecosystem marketplace, extending the base and boundaries of our platform while infusing intelligence through every step of our partners' and customers' journey. The new ecosystem enables packaging, publishing, and listing solutions across multiple technologies — Agentforce, MuleSoft, Tableau, and Slack — while delivering full transactability (Discover → Purchase → Provision). The One AppExchange Framework is our dynamic, extensible data and services platform that expands the tenancy capabilities of the AgentExchange site. This is not a search-maintenance role. You will own the technical vision for discovery at scale, drive AI-native engineering across the search stack, and set the bar for relevance, latency, personalization, and observability across one of the most strategically important surfaces in the AgentExchange. What You'll Do: Lead architectural design and delivery of major Search & Personalization capabilities, including: GenAI search — AI overview results, next-best query suggestions, and 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 within Agentforce, Slack, Setup, and other core product surfaces Search indexer — scalable, low-latency indexing pipelines for new asset types including standards-based agents, MCP tools/resources, skills, subagents, and A2A listings Champion AI-native engineering — actively use and promote AI tools across the development lifecycle, from code completion to production monitoring. Model AI fluency and help build an AI-native team culture. Define the Northstar architecture for the Search & Personalization domain — leading discovery, design, and execution tracks that align with the broader AgentExchange one-marketplace strategy. Drive platform modernization — contribute to the migration off Heroku and onto Falcon, including the enabling roadmap for search services infrastructure migration. Own engineering excellence across the search stack: 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 your domain — providing guidance, mentorship, and sponsorship to senior and junior engineers, 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 — embody our values of Trust, Innovation, Engineering Commitment, and Curiosity. Challenge the status quo and build the best-engineered solutions. 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: Search engine internals: indexing pipelines, ranking, query understanding, relevance tuning Search infrastructure: Elasticsearch, OpenSearch, Solr, or equivalent Back End: 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. Preferred Qualifications: 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 — 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. Proficient in written and spoken English. Our Engineering Values: We hold ourselves to a high standard — because our partners and customers depend on us: Trust by default — secure, accessible, performant, and scalable in everything we build. Engineering Commitment — observability, performance, and security are first-class citizens, not afterthoughts.