Forward-Deployed AI Analytics Engineer

Socket.dev; Dallas (TX); On-site; USD 150,000 - 190,000; Full time

Job summary

Salesforce seeks a Forward Deployed Engineer to lead the implementation of agentic analytics across Tableau Next, Cloud and Salesforce Data360. You will partner with strategic customers to architect and deploy their first agentic analytics use cases and supporting dashboards.

You will build semantic data models, integrate diverse data sources, and guide customers to self-sufficiency while collaborating with Product and Engineering to improve features for enterprise deployments.

Qualifications

• 7+ years of technical experience in data engineering, analytics implementation, or software development.
• Experience with data lakehouse architectures and SQL data modeling.
• Practical experience with LLMs, RAG, or conversational AI.
• Understanding semantic modeling (semantic layers/ontologies).
• Python programming and API integrations.
• AI coding/agentic harnesses for iterative development.

Responsibilities

• Architect and deploy conversational analytics agents.
• Design semantic data models in Salesforce Data360.
• Accelerate customer time-to-value during implementation.
• Integrate data from multiple sources into the Data360 lakehouse.
• Bridge product and customer feedback with stakeholders.
• Mentor customer data teams for self-sufficiency.
• Troubleshoot architectures and performance bottlenecks.

Skills

Data engineering

Data lakehouse

Python

APIs

AI/NLP

Semantic modeling

LLMs/RAG

Problem solving

Communication

Tableau integration

Tools

Tableau

Salesforce Data360

API gateways

iPaaS

Job description

Salesforce seeks a Forward Deployed Engineer to lead the implementation of agentic analytics across Tableau Next, Cloud and Salesforce Data360. You will partner with strategic customers to architect and deploy their first agentic analytics use cases and supporting dashboards.

You will build semantic data models, integrate diverse data sources, and guide customers to self-sufficiency while collaborating with Product and Engineering to improve features for enterprise deployments.