Senior Data Platform Architect – AI & Telemetry

Relha LLC; San Francisco, Northern (CA, KY); Hybrid; USD 210,000 - 320,000; Full time

Job summary

Salesforce is seeking a Software Engineering PMTS - Data Platform leader to own the data and intelligence architecture for AgentExchange. You will consolidate telemetry pipelines, define contracts, and architect the LLM-native layer for marketplace data to power partner and customer experiences.

You will engage executive stakeholders, guide cross-org reviews, and set long-term technical direction for data engineers and ML practitioners across the team.

Qualifications

• 10+ years in software / data engineering, including ownership of enterprise-scale data or ML platform.
• Deep architecture experience in lakehouse/warehouse design, streaming + batch pipelines, dimensional modeling.
• Cloud-native data infrastructure experience with Snowflake, BigQuery, Redshift, Databricks, AWS.
• LLM systems in production: RAG, embeddings, vector stores, evaluation, cost and latency tuning.

Responsibilities

• Own end-to-end data architecture and 18-month roadmap for the AgentExchange data platform.
• Lead pipelines, schema governance, and data contracts across engineering teams.
• Build self-service analytics with dashboards and partner metrics on Data 360 and Tableau Next.
• Architect the ML platform including feature store, training/serving, and model monitoring.

Skills

Executive communication

Architectural leadership

Cloud architecture

Data engineering

ML platforms

LLM/agent protocols

Education

Technical degree

Tools

Snowflake

BigQuery

Redshift

Databricks

AWS

Job description

Salesforce is seeking a Software Engineering PMTS - Data Platform leader to own the data and intelligence architecture for AgentExchange. You will consolidate telemetry pipelines, define contracts, and architect the LLM-native layer for marketplace data to power partner and customer experiences.

You will engage executive stakeholders, guide cross-org reviews, and set long-term technical direction for data engineers and ML practitioners across the team.