Director-technology - Salesforce

AT&T AT&T · Telecom · USA:TX:Plano +1

Director-level role focused on architecting and delivering enterprise-scale, AI-driven Salesforce solutions within a telecom environment. This role involves CRM transformation, legacy modernization, and integrating AI/ML, automation, and generative AI into core platform design and development, as well as applying AI-driven analytics for business insights. The position also requires managing data migrations, building data pipelines, defining API strategies, and enforcing compliance.

What you'd actually do

  1. Architect and implement scalable, high-availability Salesforce solutions supporting large subscriber data volumes
  2. Lead migration from legacy CRM and telecom platforms into a unified Salesforce architecture
  3. Embed AI/ML, automation, and generative AI into core platform design and development
  4. Design and manage large-scale data migrations (ETL, data quality, validation, and governance)
  5. Build real-time and batch data pipelines for billing, usage, and customer data

Skills

Required

  • 10+ years in enterprise architecture, including Salesforce transformation leadership
  • Proven experience migrating legacy systems to Salesforce at scale
  • Deep expertise in Salesforce architecture, data modeling, and performance optimization
  • Strong telecom domain experience (BSS/OSS, billing, network systems integration)
  • Experience with API design, event-driven architecture, and middleware (e.g., MuleSoft)
  • Hands-on knowledge of Generative AI, RAG, MCP, and predictive analytics applications
  • Experience handling high-volume, real-time data processing environments
  • Salesforce Certified Application Architect or System Architect
  • Salesforce Platform Developer II

What the JD emphasized

  • AI/ML, automation, and generative AI into core platform design and development
  • AI-driven analytics for churn prediction, outage detection, and demand forecasting
  • Generative AI, RAG, MCP, and predictive analytics applications

Other signals

  • embedding AI/ML, automation, and generative AI into core platform design and development
  • Apply AI-driven analytics for churn prediction, outage detection, and demand forecasting
  • Hands-on knowledge of Generative AI, RAG, MCP, and predictive analytics applications
  • Drive DevOps, CI/CD, and AI-assisted development to improve delivery speed and quality