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Principal Member of Technical Staff - Java + Node.Js (GenAI search)

Salesforce · Posted Oct 16

Customer relationship management, cloud computing, enterprise software, and artificial intelligence solutions

India - BangaloreFull-timeHybridLead/Staff10+ years₹80.0L–₹1.4Cr yearly34 applicants
Cloud ComputingEnterprise SoftwareCustomer Relationship ManagementArtificial IntelligenceSaaSPublic Company
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About the role

The AgentExchange Search & Personalization team builds the AI-powered discovery layer at the heart of the Salesforce ecosystem marketplace, extending embedded discovery surfaces across Agentforce, Slack, and Setup. The platform spans packaging, publishing, listing, and transactability across Agentforce, MuleSoft, Tableau, and Slack. This role owns the technical vision for GenAI search, multi-turn agentic search, personalization, contextual discovery services, and scalable search indexing infrastructure built on Java and Node.js back ends.

What you will do

  • Architectural Leadership: 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.
  • AI-Native Engineering: 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.
  • Domain Strategy & Vision: Define the Northstar architecture for the Search & Personalization domain — leading discovery, design, and execution tracks that align with the broader AgentExchange one-marketplace strategy.
  • Platform Modernization: Drive platform modernization — contribute to the migration off Heroku and onto Falcon, including the enabling roadmap for search services infrastructure migration.
  • Engineering Excellence: 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.
  • Technical Authority & Mentorship: 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.
  • Cross-Functional Collaboration: 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.
  • Culture Carrier: Be a culture carrier — embody our values of Trust, Innovation, Engineering Commitment, and Curiosity. Challenge the status quo and build the best-engineered solutions.

Skills used in this role

JavaNode.jsElasticsearchOpenSearchSolrLLMGenAIMCPA2ACI/CDHerokuFalconAgentforceSlackMuleSoftTableauSemantic SearchPersonalizationRecommendation SystemsObservabilityCommunication

What the employer is looking for

  • Experience: 10+ years of experience in software engineering, with a demonstrated track record of technical leadership on enterprise-scale search, recommendation, or personalization systems.
  • Technical Vision: Proven ability to define and drive long-term technical vision and architectural roadmaps for large, complex search or ML-infused platform domains.
  • Search System Expertise: 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.
  • Recommendation Systems: Experience designing and delivering recommendation or personalization systems — collaborative filtering, content-based ranking, behavioral signal processing, or equivalent.
  • GenAI & LLM Integration: Hands-on experience integrating LLMs or GenAI into search products — AI-generated summaries, query expansion, semantic search, or conversational retrieval.
  • Data Pipelines: Experience with real-time and near-real-time data pipelines for indexing and signal ingestion.
  • Production Reliability: Strong commitment to engineering excellence: observability, telemetry, latency SLOs, CI/CD, service ownership, safe change practices, and production reliability.
  • Communication & Influence: Excellent communication skills — able to influence and build consensus across engineering, product, and executive stakeholders.

Preferred qualifications

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

Benefits and support

  • Compensation and benefits are detailed in the job posting

About Salesforce

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Salesforce

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Salesforce, Inc. is a leading global cloud-based enterprise software company specializing in customer relationship management (CRM) and artificial intelligence solutions. Through its integrated Customer 360 platform, the company provides applications for sales, customer service, marketing automation, e-commerce, and analytics. Powered by innovations like Agentforce, Salesforce helps businesses bridge human capability with autonomous AI agents to drive customer success.

Industry
Cloud Computing
Company size
87000+ employees
Founded
1999
Location
San Francisco, California, USA
Funding stage
Public Company

Funding

Public Company · $25B raised

Emergence CapitalMeritech Capital PartnersSunBridgeStarboard ValueWilliam Hambrecht
  • 2026-03Post-IPO Debt$25B
  • 2003-01Venture Round$1M
  • 2001-06Series D$46.9M
  • 1999-11Series C$13.2M
  • 1999-06Series B$3.8M

Leadership

MB
Marc Benioff

Chair, Chief Executive Officer & Co-Founder

RW
Robin Washington

President & Chief Operating and Financial Officer

PH
Parker Harris

Co-Founder & Chief Technology Officer, Slack

DS
David Schmaier

President & Chief Strategy Officer

Recent coverage

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