Afd360 Solution Engineer - Regulated Industries

Salesforce Salesforce · Enterprise · San Francisco, CA

Salesforce is seeking a Solution Engineer for their AFD360 team, focusing on AI CRM solutions for regulated industries. This role involves being a customer-facing technical advisor and hands-on builder, guiding customers through the lifecycle of operationalizing AI agents and Data Cloud solutions. The primary goal is to help customers become Agentic Enterprises by integrating Data, AI, and Trust, from technical evaluation to production-grade deployment and scaling.

What you'd actually do

  1. Design and run workshops, demos, and time-boxed POCs/pilots—scope the work, define success metrics, execute, and deliver a clean handoff to production lanes
  2. Lead deep technical + business discovery to scope MVP agentic use cases—translate outcomes/ROI into an executable architecture and activation plan
  3. Build secure, scalable Agentforce + Data Cloud solutions to validate technical feasibility and production readiness
  4. Drive activation—partner with customers on agent definition, configuration, and deployment strategy to accelerate production readiness
  5. De-risk the path to value—assess feasibility across data, security/compliance, orchestration, and operational readiness to ensure the selected use case can scale and be adopted by real users

Skills

Required

  • 7+ years customer-facing solution/technical architecture (pre-sales, consulting, implementation) with increasing scope/influence.
  • Hands-on Agentforce (AI) and Data Cloud builder who can prototype and unblock (deep expertise with platform patterns; building workflows/automation and guiding agent build and data 360 best practices).
  • Agentic + AI fluency: practical understanding of LLMs, RAG/grounding, evaluation concepts, and how agentic systems behave in production (safety, reliability, governance).
  • Deep discovery + MVP scoping: ability to run technical & business discovery to define MVP agentic use cases, success metrics, and a feasible execution plan.
  • Enterprise data/integration fundamentals: APIs/integration patterns, governance/security, and the ability to assess data readiness and architectural feasibility.
  • Executive + technical communication: able to lead whiteboards and communicate with developers and C-suite with equal fluency—translate architecture to outcomes/ROI.
  • Proven POC/pilot leadership: designs time-boxed proof points with measurable success criteria and clean transition to production lanes.

Nice to have

  • Deep Data Cloud specialization: ingestion, modeling/harmonization, identity resolution, activation patterns; strong data architecture vocabulary (ETL/ELT, MDM, lake vs warehouse vs OLTP/OLAP).
  • Strong engineering depth: Apex and Lightning Web Components (or equivalent) and comfort operating across the SDLC; experience with “vibe coding” tooling is a plus.
  • SQL and/or Python proficiency (Jupyter/pandas helpful) and comfort with modern cloud data platforms/analytics tooling (Snowflake/Databricks/BigQuery; Tableau/Looker/Power BI).

What the JD emphasized

  • customer-facing technical trusted advisor
  • hands-on builder
  • Agentforce (AI) and Data Cloud builder
  • Agentic + AI fluency
  • Deep discovery + MVP scoping
  • Enterprise data/integration fundamentals
  • Executive + technical communication
  • Proven POC/pilot leadership

Other signals

  • customer-facing technical advisor
  • hands-on builder
  • operationalizing Data + AI + Trust
  • build secure, scalable Agentforce + Data Cloud solutions
  • guide customers across the lifecycle