Technical Architect

About This Role

As an AI and Data Technical Architect at Salesforce, you will be a hands-on technical leader and trusted advisor, designing and operationalizing enterprise-grade data and AI architectures using Salesforce D360 and the Agentforce platform. This role involves guiding Chief Data Officers and Enterprise Architects through emerging AI solutions, ensuring customers realize the full value of the platform.

Responsibilities

• Lead pre-sales technical design by analyzing customer needs and recommending solutions aligned with Agentforce capabilities and integration with external agent frameworks.
• Shape best practices around generative AI, agent interoperability, prompt engineering, Data Cloud, and cross-platform integrations.
• Collaborate with Account Executives and Sales Engineers to build hands-on prototypes and demos using Agentforce and integrated external agents.
• Develop thought leadership content including demo templates, whitepapers, and enablement sessions focused on agent lifecycle, integration strategy, and technical effectiveness.
• Act as a central technical knowledge resource, proactively addressing internal technical inquiries, facilitating deep technical enablement, and documenting best practices.
• Understand Agent Interoperability by mapping and integrating external agents from hyperscalers (e.g., Copilot, Gemini) into Agentforce via open standards (MCP, A2A).
• Enable Conversational & Background Agents using Agentforce Studio and Agent Builder; integrate with external channels including voice via hyperscaler APIs.
• Drive Prompt Engineering & Lifecycle Strategy, leading prompt design, testing, monitoring, and iteration; define agent lifecycle best practices.
• Advise on Data & Integration, ensuring cohesive architectures that align with compliance and governance policies.
• Own Technical Architecture Decisions, overseeing data modeling, identity resolution, real-time vs. batch patterns, data graph design, and activation strategies within D360.
• Own Technical Enablement, creating and managing accessible technical documentation, knowledge bases, and FAQ resources.

Requirements

• 7+ years of hands-on experience designing and delivering data, analytics, and AI architectures in enterprise environments
• Hands-on experience with Salesforce Agentforce and deep fluency with D360 and core Salesforce platform services
• Strong understanding of external agent ecosystems and interoperability
• Experience in prompt engineering, agent lifecycle management, and hands-on prototype development
• Experience with machine learning concepts (predictive and generative AI) and ability to communicate value
• Deep expertise in modern cloud data platforms (Snowflake, Databricks, BigQuery, Redshift) and data ingestion patterns
• Proficiency in programming (e.g., JavaScript, Python, SQL, R) and data frameworks like pandas or Jupyter
• Strong presentation skills; adept at explaining complex ideas and guiding stakeholders toward impactful solutions
• Passion for exploring new AI frameworks, sharing insights, and experimenting with cutting-edge technologies

Qualifications

• BS in Computer Science, Engineering, Data Science, or equivalent technical field.
• 7+ years of hands-on experience designing and delivering data, analytics, and AI architectures in enterprise environments.

Nice to Have

• Experience integrating Salesforce with external agents via APIs and open standards (MCP, A2A)
• Familiarity with prompt governance, observability, and monitoring frameworks
• Background in cross-platform integrations (e.g., Hyperscaler SDKs to Salesforce Flows)
• Prior exposure to conversational voice pipelines or multimodal integrations via hyperscaler services
• Exposure to frameworks (TensorFlow, PyTorch), MLOps practices, and cloud AI platforms like Google Vertex AI or AWS Sagemaker

Skills

* Required skills

Benefits