Salesforce is the #1 AI CRM, focused on driving customer success through innovation and trust. The AFD360 Solution Engineer will act as a trusted advisor, leading technical discovery and guiding customers in operationalizing Data, AI, and Trust to achieve successful outcomes.
Responsibilities:
- 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
- Lead deep technical + business discovery to scope MVP agentic use cases—translate outcomes/ROI into an executable architecture and activation plan
- Build secure, scalable Agentforce + Data Cloud solutions to validate technical feasibility and production readiness
- Drive activation—partner with customers on agent definition, configuration, and deployment strategy to accelerate production readiness
- 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
- Serve as an expert technical overlay for internal teams and customers—accelerate scalable agent builds while enabling a self-sufficient agentic capability through reusable patterns, guardrails, and enablement
- Evangelize Agentforce enablement across REG—socialize current capabilities, roadmap updates, and best practices; capture and scale field learnings
- Work closely with Product, FDE, and cross-OU AI SMEs to continuously sharpen technical depth, close skill gaps, and influence roadmap through structured feedback loops
- Identify automation and process improvement opportunities—intake both process and technical requirements to remove friction and accelerate activation
- Monitor early consumption/performance; advise on optimization and consumption plan updates
- Understand consumption levers and model anticipated consumption spend based on architecture and usage patterns
- Own a crisp POC→production transition—coordinate accountable delivery lanes (customer CoE, SI, ProServ, FDE, CS) and execute clean handoffs to ensure durable activation and scalable outcomes
- Build reusable accelerators (POC assets, playbooks, best practices) and enable others to scale delivery
- Drive Voice of the Customer into Product; inform messaging/plays with Product Marketing
- Represent Salesforce at customer/industry events (Dreamforce, World Tours, etc.)
Requirements:
- 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
- Growth mindset: willingness to continually sharpen technical/advisory skills through required enablement, labs, courses, and certifications
- 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)
- Experience with other agent platforms (e.g., Gemini/Agentspace or similar) and broader AI automation implementations
- Consumption/business modeling: understands consumption levers and can map anticipated consumption spend from architecture/usage patterns (especially valuable for internal candidates)
- Regulated industry background: HLS and/or FINS experience strongly preferred
- Salesforce certifications (AI Specialist, Data Cloud Consultant, Admin/Advanced Admin, App Dev)