salesforce.com, inc.
Director, Engineering - Agentic Search & AI Components
salesforce.com, inc., Seattle, Washington, us, 98127
What You’ll Do
Architect Search & Retrieval Systems: Design and implement robust search indices that enable AI agents to perform complex retrievals across the Salesforce data ecosystem.
Lead AI Component Development: Oversee the creation of the semantic layer and embedding pipelines necessary for grounding Agentic AI in Customer Success data.
Team Leadership: Lead, mentor, and manage a high‑performing team of data and AI engineers, fostering technical excellence and career growth.
Strategic Roadmap: In partnership with product managers, define the technical vision for agentic retrieval, aligning search strategy with the broader migration to Data Cloud and the evolution of AI‑driven personalized engagements.
Operational Excellence: Establish rigorous standards for data quality, latency, and index freshness to ensure agents provide reliable, real‑time insights.
Cross‑Functional Collaboration: Partner with Data Scientists, Product Managers, and the other engineering leaders to translate complex business needs into scalable technical solutions.
AI Integration & Automation: Lead efforts to automate the data delivery pipeline, ensuring seamless integration between internal databases, third‑party APIs, and the AI orchestration layer.
What We’re Looking For
A related technical degree required.
Professional Experience: 10+ years in engineering, with a significant focus on search technology, vector databases, data engineering, and AI/ML infrastructure.
Technical Proficiency: Deep expertise in Search Indices (e.g., Pinecone, Milvus, Redis); Experience with Workflow Orchestration tools like Airflow or dbt; Strong programming skills in Python, Java, or Scala, and experience with data frameworks like Spark and Pandas/Polars; Hands‑on experience with Cloud Platforms (AWS, Azure) and modern data warehousing (BigQuery, Redshift, Data Cloud); Hands‑on experience with the Salesforce ecosystem (Data360, Agentforce, Service Cloud, etc.).
AI & Data Science Domain Knowledge: Understanding of embedding models, LLM grounding techniques, and semantic layer construction.
Soft Skills: Exceptional ability to communicate complex technical concepts (like vector similarity or RAG architecture) to non‑technical stakeholders.
Leadership Track Record: Proven experience managing engineering teams in a fast‑paced, enterprise environment.
Accommodations If you require assistance due to a disability applying for open positions please submit a request via this Accommodations Request Form.
Posting Statement Salesforce is an equal opportunity employer and maintains a policy of non‑discrimination with all employees and applicants for employment. What does that mean exactly? It means that at Salesforce, we believe in equality for all. And we believe we can lead the path to equality in part by creating a workplace that’s inclusive, and free from discrimination. Any employee or potential employee will be assessed on the basis of merit, competence and qualifications – without regard to race, religion, color, national origin, sex, sexual orientation, gender expression or identity, transgender status, age, disability, veteran or marital status, political viewpoint, or other classifications protected by law. This policy applies to current and prospective employees, no matter where they are in their Salesforce employment journey. It also applies to recruiting, hiring, job assignment, compensation, promotion, benefits, training, assessment of job performance, discipline, termination, and everything in between. Recruiting, hiring, and promotion decisions at Salesforce are fair and based on merit. The same goes for compensation, benefits, promotions, transfers, reduction in workforce, recall, training, and education.
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Architect Search & Retrieval Systems: Design and implement robust search indices that enable AI agents to perform complex retrievals across the Salesforce data ecosystem.
Lead AI Component Development: Oversee the creation of the semantic layer and embedding pipelines necessary for grounding Agentic AI in Customer Success data.
Team Leadership: Lead, mentor, and manage a high‑performing team of data and AI engineers, fostering technical excellence and career growth.
Strategic Roadmap: In partnership with product managers, define the technical vision for agentic retrieval, aligning search strategy with the broader migration to Data Cloud and the evolution of AI‑driven personalized engagements.
Operational Excellence: Establish rigorous standards for data quality, latency, and index freshness to ensure agents provide reliable, real‑time insights.
Cross‑Functional Collaboration: Partner with Data Scientists, Product Managers, and the other engineering leaders to translate complex business needs into scalable technical solutions.
AI Integration & Automation: Lead efforts to automate the data delivery pipeline, ensuring seamless integration between internal databases, third‑party APIs, and the AI orchestration layer.
What We’re Looking For
A related technical degree required.
Professional Experience: 10+ years in engineering, with a significant focus on search technology, vector databases, data engineering, and AI/ML infrastructure.
Technical Proficiency: Deep expertise in Search Indices (e.g., Pinecone, Milvus, Redis); Experience with Workflow Orchestration tools like Airflow or dbt; Strong programming skills in Python, Java, or Scala, and experience with data frameworks like Spark and Pandas/Polars; Hands‑on experience with Cloud Platforms (AWS, Azure) and modern data warehousing (BigQuery, Redshift, Data Cloud); Hands‑on experience with the Salesforce ecosystem (Data360, Agentforce, Service Cloud, etc.).
AI & Data Science Domain Knowledge: Understanding of embedding models, LLM grounding techniques, and semantic layer construction.
Soft Skills: Exceptional ability to communicate complex technical concepts (like vector similarity or RAG architecture) to non‑technical stakeholders.
Leadership Track Record: Proven experience managing engineering teams in a fast‑paced, enterprise environment.
Accommodations If you require assistance due to a disability applying for open positions please submit a request via this Accommodations Request Form.
Posting Statement Salesforce is an equal opportunity employer and maintains a policy of non‑discrimination with all employees and applicants for employment. What does that mean exactly? It means that at Salesforce, we believe in equality for all. And we believe we can lead the path to equality in part by creating a workplace that’s inclusive, and free from discrimination. Any employee or potential employee will be assessed on the basis of merit, competence and qualifications – without regard to race, religion, color, national origin, sex, sexual orientation, gender expression or identity, transgender status, age, disability, veteran or marital status, political viewpoint, or other classifications protected by law. This policy applies to current and prospective employees, no matter where they are in their Salesforce employment journey. It also applies to recruiting, hiring, job assignment, compensation, promotion, benefits, training, assessment of job performance, discipline, termination, and everything in between. Recruiting, hiring, and promotion decisions at Salesforce are fair and based on merit. The same goes for compensation, benefits, promotions, transfers, reduction in workforce, recall, training, and education.
#J-18808-Ljbffr