Overview

As an AI and Data Technical Architect, you will lead high-impact, enterprise-grade data and AI solutions centered on Salesforce D360 and the Agentforce platform. You’ll guide senior customers and cross-functional teams to design scalable, secure architectures that integrate with complex ecosystems. You will shape AI best practices, deliver hands-on prototypes, and enable teams through documentation and enablement. This role blends data engineering, platform architecture, and applied AI to drive customer value and transformation.

Responsabilidades

- Lead pre-sales technical design by analyzing customer needs and mapping solutions to Agentforce capabilities and external integrations.
- Define best practices for generative AI, agent interoperability, prompt engineering, Data Cloud, and cross-platform integrations.
- Collaborate with AEs and SEs to build hands-on prototypes and demos using Agentforce and connected external agents.
- Create thought leadership content (templates, whitepapers, enablement sessions) on agent lifecycle, integration strategy, and technical effectiveness.
- Serve as a central technical knowledge resource, addressing inquiries and enabling specialist teams with documentation of best practices.
- Map and integrate external agents from hyperscalers into Agentforce via open standards; design collaboration.
- Configure chat and background agents with Agentforce Studio/Agent Builder; integrate with hyperscaler APIs for voice channels.
- Lead prompt design, testing, monitoring, and lifecycle strategies for agents; establish lifecycle best practices.
- Co-create quick prototypes (<2 weeks)



with AEs showing Agentforce integration with external agents or services.
- Facilitate pre-sales workshops and deep-dive sessions for customers and internal teams.
- Advise on Data & Integration to align Data Cloud (D360), CRM, MuleSoft APIs, and external endpoints with governance policies.
- Support early adoption and proof-of-value engagements by tuning agents and guiding self-sufficient enablement.
- Oversee data modeling, identity resolution, real-time vs. batch patterns, data graph design, and activation within D360.
- Create accessible technical documentation, knowledge bases, and FAQs to empower teams.

Requisitos principales

- 7+ years of hands-on experience designing and delivering data, analytics, and AI architectures in enterprise environments.
- Strong understanding of external agent ecosystems and interoperability.
- Proven track record in prompt engineering, agent lifecycle management, and prototype development.
- Experience with machine learning concepts (predictive and generative AI) and ability to communicate value to diverse audiences.
- Deep expertise in modern cloud data platforms (Snowflake, Databricks, BigQuery, Redshift) and data ingestion patterns (batch, streaming, CDC).
- Proficiency in programming (JavaScript, Python, SQL, R) and data frameworks like pandas or Jupyter.
- Excellent communication and ability to guide stakeholders toward impactful solutions.
- Curiosity and continuous learning mindset with interest in new AI frameworks.

- Excellent communication
- Curiosity / Learning
- Collaborative mindset
- Salesforce Agentforce and D360 familiarity
- External agent ecosystems and interoperability
- Prompt engineering and agent lifecycle management

📌 Principle AI Architect (Barcelona)
🏢 Salesforce
📍 Barcelona