Overview
Asegúrese de leer detenidamente la información sobre esta ocasión antes de presentar su candidatura.
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 ( 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. xqbhyrx
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