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AFD360 Solution Engineer - Regulated Industries
California
1 month ago
💻 Open SourceMentions "vibe coding" tooling as a plus, indicating familiarity with vibe coding workflows is helpful.
About the Role
Customer-facing Solution Engineer focused on enabling regulated-industry customers to operationalize Data + AI using Salesforce Agentforce and Data Cloud. Lead technical discovery, prototype and run time-boxed POCs, and drive production readiness, activation, and scalable adoption.
Job Description
Role
The AFD360 Solution Engineer (Regulated Industries) is a customer-facing technical advisor and hands-on builder who serves as the SME for Agentforce and Data Cloud. The role leads technical discovery, designs and executes pilots/POCs, validates production readiness, and drives activation and consumption across customers in regulated industries.
Key Responsibilities
- Lead technical and business discovery to define MVP agentic use cases, success metrics, and executable architecture/activation plans.
- Design and run workshops, demos, and time-boxed POCs/pilots; scope work, define success criteria, execute, and hand off to production lanes.
- Build secure, scalable Agentforce + Data Cloud solutions to validate feasibility and production readiness.
- Drive activation by partnering with customers on agent definition, configuration, and deployment strategy.
- Assess feasibility across data, security/compliance, orchestration, and operational readiness to de-risk production adoption.
- Serve as a technical overlay for internal teams and customers; create reusable patterns, guardrails, playbooks, and accelerators.
- Monitor early consumption/performance and advise on optimization and consumption modeling based on architecture and usage.
- Coordinate POC-to-production transitions and accountable delivery lanes (customer CoE, SI, ProServ, FDE, CS).
- Evangelize Agentforce and Data Cloud capabilities, capture field learnings, and inform product/marketing through VoC.
Requirements
Required
- 7+ years of customer-facing solution/technical architecture experience (pre-sales, consulting, implementation).
- Hands-on experience building with Agentforce (AI) and Data Cloud; able to prototype and unblock implementations.
- Practical understanding of LLMs, RAG/grounding, evaluation concepts, and production behavior of agentic systems (safety, reliability, governance).
- Strong discovery and MVP scoping skills; ability to translate outcomes/ROI into executable architectures.
- Enterprise data/integration fundamentals (APIs/integration patterns, governance, security) and ability to assess data readiness.
- Executive and technical communication skills across developers and C-suite.
- Proven leadership of POCs/pilots with measurable success criteria and clean production transitions.
- Growth mindset and willingness to complete enablement, labs, courses, and certifications.
Preferred
- Deep Data Cloud specialization: ingestion, modeling/harmonization, identity resolution, activation patterns, and data architecture vocabulary (ETL/ELT, MDM).
- Engineering experience with Apex and Lightning Web Components; familiarity with SDLC practices.
- SQL and/or Python proficiency; familiarity with Jupyter and pandas.
- Experience with modern cloud data platforms and analytics tooling (Snowflake, Databricks, BigQuery, Tableau, Looker, Power BI).
- Experience with other agent platforms and broader AI automation implementations.
- Consumption/business modeling experience to map anticipated consumption spend from architecture/usage.
- Regulated industry experience (HLS and/or FINS) and relevant Salesforce certifications (AI Specialist, Data Cloud Consultant, Admin/Advanced Admin, App Dev).