Principal Technical Architect, Agentforce

Agentforce is Salesforce's newest innovation—a next-generation platform that combines Data + AI + CRM + Trust to transform customer experiences. Our Agentforce specialist team is a startup within a global organization, dedicated to helping Salesforce customers and prospects design and implement cutting-edge solutions that deliver real business value. This innovative group partners closely with our Product, Product Marketing, Enablement, Customer Success, and Partner Ecosystem to drive growth and adoption of Agentforce.

Role Description

• As an Agentforce Technical Architect, you'll act as a trusted advisor to our customers, guiding them through the emerging AI solutions and ensuring they realize the full value of the platform. You'll combine deep technical domain expertise in AI/ML, data infrastructure, and CRM with strong presentation and solutioning skills. Working side by side with our Account Executives, Solutions Engineers, Product, and Product Marketing teams, you will:

• Provide technical leadership during pre-sales by assessing customer use cases, recommending optimal solutions, and shaping the overall technical vision for Agentforce within their ecosystem.

• Champion standard methodologies around AI/ML (including agent-based models, predictive, and generative AI), data pipelines, and the Salesforce platform to drive innovation and customer adoption.

• Create and deliver relevant content—demos, videos, white-papers, enablement sessions—to both internal and external audiences, establishing yourself as a leader with vision for Agentforce.

If you are naturally curious about AI, love diving into new technologies, and enjoy educating others while crafting solutions that deliver real business impact, we want to talk to you

Responsibilities

• Tackle Sophisticated Problems: Research customer challenges, architect innovative AI/ML solutions, and drive key technical decisions.

• Drive Adoption & Value: Facilitate partner alignment on high-impact use cases that leverage AI, data pipelines, and Agentforce.

• Showcase Real-World Solutions: Partner with Sales and Solutions Engineering to build compelling demos and prototypes that illustrate immediate ROI and practical use.

• Facilitate Workshops & Education: Lead white-boarding sessions, training, and hands-on workshops to help customers and internal teams understand AI opportunities and challenges.

• Develop Cross-Platform Solutions: Integrate data cloud, CRM, analytics tools, and cloud services (REST APIs, SDKs, data pipelines) into scalable, cohesive architectures.

• Lead Technical Thought Leadership: Produce best-practice documentation, architectural diagrams, and enablement materials that highlight emerging AI trends and Agentforce innovations.

Requirements

• Technical Pre-Sales/Consulting: Several years in solutions engineering, architecture, or technical consulting, ideally in B2B SaaS.

• AI & ML Expertise: Experience with machine learning concepts (predictive and generative AI), plus the ability to communicate value to diverse audiences.

• CRM & Data Knowledge: Familiarity with Salesforce CRM and modern data stacks; comfortable discussing governance, security, and integration.

• REST APIs & SDKs: Proven track record to leverage APIs and SDKs to build robust, scalable solutions.

• Hands-On Development: Proficiency in programming (e.g., JavaScript, Python, SQL) or Salesforce development (Apex, Lightning Web Components, etc.).

• Excellent Communication: Strong presentation skills; adept at explaining sophisticated ideas and guiding partners toward impactful solutions.

• Curiosity & Continuous Learning: Passion for exploring emerging AI research, frameworks, sharing insights, and experimenting with innovative technologies. Actively stays up to date on new LLM models and agentic approaches, experimenting with prompt engineering to drive innovation.

Preferred Requirements

• Agentforce or Salesforce CRM: Experience with Agentforce, Data Cloud, or Salesforce products (Sales Cloud, Service Cloud, Heroku).

• Data & Cloud Platforms: Familiarity with databases (Snowflake, Databricks), ETL processes, and cloud providers (AWS, Azure, GCP).

• Advanced AI/ML: Exposure to frameworks (TensorFlow, PyTorch), MLOps practices, and cloud AI platforms (e.g., Google Vertex AI, AWS Sagemaker). Hands-on work with Generative AI, Large Language Models (LLMs), agent-based frameworks, and prompt engineering.

NOTE: This role is office-flexible, and the expectation is to be in-office a minimum of 3 days per week.

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