Data & AI Architect
Salary not listed • United Kingdom - London • Full-time
Posted 9d ago
Job Location
United Kingdom - London
Tech Stack
Remote Work Policy
On-site
Employment Type
Full-time
Categories
AI Engineer
About the job
As an AI and Data Technical Architect, you will serve as a senior, hands-on technical leader and trusted advisor to customers. Your primary responsibility will be designing, validating, and operationalizing enterprise-grade data and AI architectures, with a focus on Salesforce D360 and the Agentforce platform. This role bridges data engineering, platform architecture, and applied AI, requiring you to guide Chief Data Officers and Enterprise Architects through emerging AI solutions. You will collaborate closely with Account Executives and Product teams to ensure customers maximize the platform's value by architecting scalable, secure solutions that integrate D360 into complex enterprise ecosystems, including hyperscalers, data lakes, and governance frameworks.
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 AEs and SEs 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.
- Map and integrate external agents from hyperscalers (e.g., Copilot, Gemini) into Agentforce via open standards (MCP, A2A), designing how these systems collaborate.
- Configure chat and background agents using Agentforce Studio and Agent Builder, integrating with external channels including voice via hyperscaler APIs.
- Lead prompt design, testing, monitoring, and iteration, defining agent lifecycle best practices from development through refinement.
- Co-create quick prototypes (<2 weeks) with AEs demonstrating integration between Agentforce and external agents or services.
- Facilitate whiteboarding, deep-dive sessions, and quick enablement for customers and internal teams.
- Integrate Data Cloud (D360), CRM, MuleSoft APIs, and external agent endpoints, ensuring cohesive architectures that align with compliance and governance policies.
- Assist in proof-of-value engagements post-sale by tuning agents and guiding customers toward self-sufficient enablement.
- Oversee data modeling, identity resolution, real-time vs. batch patterns, data graph design, and activation strategies within D360.
- Create and manage accessible technical documentation, knowledge bases, and FAQ resources to rapidly resolve internal technical inquiries.
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.
- Proven 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 to diverse audiences.
- Deep expertise in modern cloud data platforms (Snowflake, Databricks, BigQuery, Redshift) and data ingestion patterns (batch, streaming, CDC).
- Proficiency in programming languages such as JavaScript, Python, SQL, R, and data frameworks like pandas or Jupyter.
- Strong presentation skills and ability to explain complex ideas and guide stakeholders toward impactful solutions.
- Passion for exploring new technologies and continuous learning.