To get the best candidate experience, please consider applying for a maximum of 3 roles within 12 months to ensure you are not duplicating efforts.
As an AFD360 SE, you are a customer-facing technical trusted advisor and hands-on builder. You will lead technical discovery, shape and execute proof points in customer environments, guide production readiness, and establish a clear path to activation and consumption—blending executive presence with deep, full-stack technical skills across Salesforce, modern data architectures, and AI.
The AFD360 SE (Agentforce + Data Cloud) is focused on a single transformative goal: helping customers become a true Agentic Enterprise by operationalizing Data + AI + Trust. You will serve as a definitive SME for Agentforce and Data Cloud and guide customers across the lifecycle—from technical evaluation and close through activation, adoption, and expansion.
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 POCproduction 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.)
B.S. Computer Science, Software Engineering, MIS
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 7vibe coding8 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).
