Principal AI Architect

Jobtailor; Madrid; Presencial; EUR 120.000 - 150.000; Jornada completa

Descripción de la vacante

Jobtailor is seeking a senior hands-on technical leader to architect and deliver enterprise data and AI architectures centered on Salesforce D360 and Agentforce. You will guide CIOs and enterprise architects, shape best practices, and collaborate with sales and product teams to design scalable, secure solutions.

Build prototypes, create demos and enable customer teams across Spanish and English contexts. You will drive integration with external agent ecosystems, manage prompts and lifecycle, and

Formación

• 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.
• Experience in prompt engineering, agent lifecycle management, and hands-on prototype development.
• Experience with machine learning concepts, including predictive and generative AI.
• Deep expertise in Snowflake, Databricks, BigQuery, Redshift, and data ingestion patterns including batch, streaming, and CDC.
• Proficiency in JavaScript, Python, SQL or R.
• Experience with pandas or Jupyter.
• Excellent presentation and communication skills.
• Strong communication skills in both Spanish and English.

Responsabilidades

• Act as a senior, hands-on technical leader and trusted advisor to customers.
• Design, validate, and operationalize enterprise‑grade data and AI architectures centered on Salesforce D360 and Agentforce.
• Guide Chief Data Officers and Enterprise Architects through emerging AI solutions.
• Collaborate with Account Executives and Product teams on scalable, secure solutions integrating D360 with enterprise ecosystems.
• Lead pre‑sales technical design and recommend Agentforce‑aligned solutions.
• Shape best practices for generative AI, agent interoperability, prompt engineering, Data Cloud, and cross‑platform integrations.
• Build hands‑on prototypes and demos with Account Executives and Sales Engineers.
• Develop thought leadership content, demo templates, whitepapers, and enablement sessions.
• Serve as a central technical knowledge resource and document best practices.
• Map and integrate external hyperscaler agents such as Copilot and Gemini into Agentforce using MCP and A2A.
• Configure conversational and background agents using Agentforce Studio and Agent Builder.
• Design, test, monitor, and iterate prompts and define agent lifecycle practices.
• Co‑create prototypes in under two weeks.
• Facilitate customer and internal pre‑sales workshops and technical enablement.
• Integrate Data Cloud, CRM, MuleSoft APIs, and external agent endpoints.
• Support post‑sale proof‑of‑value engagements by tuning agents and guiding customer enablement.
• Oversee D360 data modelling, identity resolution, real‑time versus batch patterns, data graph design, and activation strategies.
• Create and manage technical documentation, knowledge bases, and FAQ resources

Conocimientos

Data architecture design

AI architecture delivery

Prototype development

Prompt engineering

Agent interoperability

JavaScript

Python

SQL

R

Pandas

Herramientas

Snowflake

Databricks

BigQuery

Redshift

MuleSoft APIs

Jupyter

TensorFlow

PyTorch

Google Vertex AI

AWS Sagemaker

Descripción del empleo

• Act as a senior, hands‑on technical leader and trusted advisor to customers
• Design, validate, and operationalize enterprise‑grade data and AI architectures centered on Salesforce D360 and Agentforce
• Guide Chief Data Officers and Enterprise Architects through emerging AI solutions
• Collaborate with Account Executives and Product teams on scalable, secure solutions integrating D360 with enterprise ecosystems
• Lead pre‑sales technical design and recommend Agentforce‑aligned solutions
• Shape best practices for generative AI, agent interoperability, prompt engineering, Data Cloud, and cross‑platform integrations
• Build hands‑on prototypes and demos with Account Executives and Sales Engineers
• Develop thought leadership content, demo templates, whitepapers, and enablement sessions
• Serve as a central technical knowledge resource and document best practices
• Map and integrate external hyperscaler agents such as Copilot and Gemini into Agentforce using MCP and A2A
• Configure conversational and background agents using Agentforce Studio and Agent Builder
• Design, test, monitor, and iterate prompts and define agent lifecycle practices
• Co‑create prototypes in under two weeks
• Facilitate customer and internal pre‑sales workshops and technical enablement
• Integrate Data Cloud, CRM, MuleSoft APIs, and external agent endpoints
• Support post‑sale proof‑of‑value engagements by tuning agents and guiding customer enablement
• Oversee D360 data modelling, identity resolution, real‑time versus batch patterns, data graph design, and activation strategies
• Create and manage 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
• 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, including predictive and generative AI
• Deep expertise in Snowflake, Databricks, BigQuery, Redshift, and data ingestion patterns including batch, streaming, and CDC
• Proficiency in JavaScript, Python, SQL, or R
• Experience with pandas or Jupyter
• Excellent presentation and communication skills
• Strong communication skills in both Spanish and English
• Passion for exploring new AI frameworks and cutting‑edge technologies
• Salesforce Agentforce, D360, and core Salesforce platform services experience preferred
• Experience integrating Salesforce with external agents via APIs, MCP, and A2A preferred
• Familiarity with prompt governance, observability, and monitoring frameworks preferred
• Experience with cross‑platform integrations preferred
• Exposure to conversational voice pipelines or multimodal integrations preferred
• Exposure to TensorFlow, PyTorch, MLOps, Google Vertex AI, or AWS Sagemaker preferred

Core Competencies

Demonstrates extensive experience in designing and operationalizing enterprise‑grade data and AI architectures, with a strong focus on Salesforce D360 and Agentforce. Proficient in prompt engineering, agent lifecycle management, and integrating external agent ecosystems.

Highest‑signal resume keywords

• Salesforce D360
• Agentforce
• Data Cloud Integration
• Prompt Engineering
• Machine Learning Concepts

ATS Optimization Keywords

Hard Skills

• Data Architecture Design
• AI Architecture Delivery
• Prototype Development
• Data Ingestion Patterns
• JavaScript
• Python
• SQL
• R
• Snowflake
• Databricks

Soft Skills

• Excellent Presentation Skills
• Strong Communication Skills

Industry Keywords

• Generative AI
• Agent Interoperability
• Cross‑Platform Integrations
• Conversational Voice Pipelines
• Multimodal Integrations

Tools & Technologies

• MuleSoft APIs
• Jupyter
• TensorFlow
• PyTorch
• Google Vertex AI
• AWS Sagemaker