Pre-sales Data and AI Architect - Solution Engineering (united States)

Salesforce Salesforce · Enterprise · New York, NY

Salesforce is seeking a Pre-Sales Data and AI Architect to design, validate, and operationalize enterprise-grade data and AI architectures centered on Salesforce D360 and the Agentforce platform. This role involves working with customer architects and data engineers to integrate D360 into complex enterprise ecosystems, owning the technical architecture end-to-end, and establishing the data foundation for trusted AI and agentic workflows. Responsibilities include hands-on technical discovery, system design, architecture validation, POC execution, and influencing product roadmaps. The role requires deep expertise in cloud data platforms, data engineering patterns, and Salesforce architecture, with a focus on customer success and driving D360 adoption.

What you'd actually do

  1. Own and drive the full technical lifecycle, from deep technical discovery and system design to architecture validation and technical close, across in-person and virtual engagements.
  2. Design and validate end-to-end data architectures integrating Salesforce D360 with enterprise systems (Snowflake, Databricks, BigQuery, Redshift, streaming platforms, MDM, and source systems).
  3. Own technical architecture decisions, including data modeling, identity resolution, real-time vs. batch patterns, data graph design, and activation strategies within D360.
  4. Partner with Account Executives to shape technical close strategy, grounded in architectural feasibility, scalability, and customer data realities.
  5. Execute hands-on technical validation (POCs, architectural walkthroughs, reference implementations) to de-risk complex deals and accelerate D360 adoption.

Skills

Required

  • 7+ years of hands-on experience designing and delivering data, analytics, and AI architectures in enterprise environments.
  • Strong background in data engineering, platform architecture, or technical architecture roles (pre-sales or post-sales).
  • BS in Computer Science, Engineering, Data Science, or equivalent technical field (advanced degree preferred).
  • Proven experience integrating complex, distributed data ecosystems with activation platforms like D360 to drive business outcomes.
  • Deep expertise in: Modern cloud data platforms (Snowflake, Databricks, BigQuery, Redshift)
  • Deep expertise in: Data ingestion patterns (batch, streaming, CDC)
  • Deep expertise in: Identity resolution, data modeling, and graph-based relationships
  • Hands-on proficiency with Python/R, data frameworks (DataFrames, pandas), and analytics workflows (Jupyter).
  • Strong technical fluency with Salesforce platform architecture, including D360 and core Salesforce services.
  • Experience guiding architectural conversations with senior technical stakeholders and influencing platform and data strategy decisions.
  • Ability to translate complex technical concepts into clear architectural guidance for both technical and executive audiences.
  • Experience operating in large, matrixed organizations with complex stakeholder environments.

Nice to have

  • advanced degree preferred

What the JD emphasized

  • agentic era
  • agentic workflows

Other signals

  • designing, validating, and operationalizing enterprise-grade data and AI architectures
  • work directly with customer architects, data engineers, and platform owners to design scalable, secure, and performant solutions
  • owns the technical architecture end-to-end
  • establish the data foundation required for trusted AI, agentic workflows, and measurable business outcomes
  • design and validate end-to-end data architectures integrating Salesforce D360 with enterprise systems
  • Partner with Account Executives to shape technical close strategy
  • Execute hands-on technical validation (POCs, architectural walkthroughs, reference implementations)
  • Define repeatable industry-specific reference architectures
  • Collaborate deeply with Salesforce Product & Engineering teams
  • Influence roadmap through high-signal Voice of the Customer feedback
  • Validate architectural patterns against upcoming D360 capabilities
  • Act as a technical authority during escalations, architecture reviews, and executive-level design discussions
  • Produce high-fidelity technical assets (architecture diagrams, Demos, governance models, activation patterns)
  • Serve as a trusted technical advisor to customer Chief Data Officers, Enterprise Architects, and Platform Owners
  • Ensure D360 architectures align to security, privacy, compliance, and trust requirements—especially in regulated industries
  • Represent Salesforce’s technical point of view for modern data and AI architectures, with D360 as the system of activation