Principal Data and AI Architect

Description

about the Team

We are a Data & AI Architects team focused on helping customers understand what this new AI era makes possible, and what it actually takes to make the possible a reality: the right architecture, a trusted data foundation, a clear operating model, and an adoption path that scales. We work in the field, close to customers, close to our Agentforce and Data 360 sellers, and close to Product, Engineering, Support, and delivery teams. We are expected to know the domain, understand the wider ecosystem, bring a strong point of view, and help guide the architectural decisions that turn AI ambition into trusted business outcomes.

We are looking for architects who love hard problems, think in systems, and are energized by the transformation AI is driving across organizations. We value people who understand how the whole landscape fits together and where Salesforce creates the most leverage within it.

About The Role

As a Data & AI Technical Architect, you are the expert thought leader and senior field specialist for customers evaluating, implementing, and expanding their use of Salesforce Data 360 (Data Cloud), Agentforce, and the broader enterprise data and AI ecosystem.

Your work sits at the intersection of technical architectural, solution engineering, applied data and AI, and delivery-aware judgment on what it takes to make a solution succeed. You help customers translate their data and AI ambitions into practical, actionable architectures. This role asks you to go both deep and wide: deep on the trusted data and agent foundation that everything else depends on, and wide across the ecosystem on which your customers actually run their business — because real architecture lives at the seams between systems, not inside any single product.

What You’ll Do

• Share a clear point of view on enterprise data and AI — how agents, data platforms, CRM, trust, identity, workflow, governance, and adoption come together into something that delivers value through Salesforce.
• Deeply understand our data & AI products and articulate the value of the Salesforce platform.
• Partner with sellers and solution teams to uncover customers' real problems, shape technical strategy, and pressure-test feasibility and cost-to-serve early.
• Lead customer architectural discussions around Data 360, Agentforce, data structures and patterns, AI readiness, identity management, governance, integration, automation, and business value.
• Build customer confidence through demos, prototypes, proofs of concept, reference patterns, and architectural walkthroughs that demonstrate what's real as well as what it will take to operationalize and scale.
• Continuously scan the horizon and tinker to refine your judgement on what's worth building and how to build within the data and AI space.
• Turn what you learn in the field into reusable assets, enablement, best practices, and product feedback that extend your impact beyond your immediate teams and stakeholders.

What You'll Bring

You are a builder as much as an advisor. You are comfortable picking up new tools and technology, and are not afraid to get hands‑on. You can craft and deliver an engaging story and also pressure-test the architecture behind it. You go deep without getting lost and wide without getting shallow. You bring field presence and credibility across a range of levels with your ability to effectively engage customer executives, enterprise architects, data platform owners, security and governance leaders, technical practitioners, sellers, partners, and delivery stakeholders.

Qualifications

• 7+ years experience in technical architecture, enterprise architecture, solution engineering, consulting, implementation, software engineering, product development, or related work in complex enterprise environments.
• A track record of shaping technical strategy with input from customers and /or stakeholders, validating solution approaches, and connecting business needs to technology decisions.
• Strong understanding of enterprise data, AI, integration, governance, security, privacy, and platform architecture concepts and patterns.
• Experience working across Sales, Product, Engineering, Support, and delivery or customer teams to move solutions from idea to execution.
• The ability to distill and communicate complex technical ideas to executive and technical audiences.
• Demonstrated curiosity and learning velocity in emerging technologies — especially within the AI, data, automation, and agentic systems space.
• Bachelor’s degree in Computer Science, Software Engineering, Electrical Engineering, Data Science, other STEM degrees or equivalent work experience. Graduate study a plus.

Helpful Experience

We care most about architectural judgment, learning velocity, and stakeholder impact. Experience with any of the following technologies and functions is a plus:

• Salesforce Data 360 (Data Cloud), Agentforce, MuleSoft, Tableau, Informatica, or the broader Salesforce Platform.
• Conversational AI, voice‑enabled AI agents, real‑time voice orchestration, telephony integrations, or multi‑channel service experiences.
• Modern data platforms such as Snowflake, Databricks, BigQuery, or RedShift, and the hyperscaler ecosystems around them.
• AI agents, generative AI, AI governance and observability, external agent ecosystems, hyperscaler AI services, or enterprise automation.
• Programming languages such as Python, common data structures and tooling, and AI‑assisted development pipelines.
• Building demos, prototypes, proofs of concept, workshops, reference architectures, or field enablement assets.

The Architect Who Thrives Here

You will thrive as part of our team if you seek to understand customers’ real problems, not just the stated requirements. You are curious about how organizations work, where data and processes break down, where AI can create leverage, and how businesses need to evolve to succeed. You are a leader who confidently defines the what, how, and why, and challenges the status quo when you see a better path. You are excited about AI while remaining grounded in what makes it work well: trusted data, clear use cases, strong architectures, governance, ado

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