Lead/Principal Data and AI Architect

Lead/Principal Data and AI Architect

Full-Time 70000 - 90000 £ / year (est.) Home office (partial)
B Capital

At a Glance

  • Tasks: Design and operationalise cutting-edge data and AI architectures for enterprise clients.
  • Company: Join a forward-thinking tech company at the forefront of AI innovation.
  • Benefits: Competitive salary, flexible working options, and opportunities for professional growth.
  • Other info: Dynamic team environment with a focus on continuous learning and innovation.
  • Why this job: Be a key player in shaping the future of AI and data solutions.
  • Qualifications: 7+ years in data architecture, Salesforce expertise, and strong programming skills.

The predicted salary is between 70000 - 90000 £ per year.

Overview of the Role

As an AI and Data Technical Architect, you will act as a senior, hands-on technical leader and trusted advisor to our customers. You will be responsible for designing, validating, and operationalizing enterprise-grade data and AI architectures centered on Salesforce D360 and the Agentforce platform. This role sits at the intersection of data engineering, platform architecture, and applied AI, requiring you to guide customer Chief Data Officers and Enterprise Architects through emerging AI solutions. You will work side by side with Account Executives and Product teams to ensure customers realize the full value of the platform by designing 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, demo templates, whitepapers, 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 to empower specialist teams across the organization.
  • Understand Agent Interoperability - Map and integrate external agents from hyperscalers (e.g., Copilot, Gemini) into Agentforce via open standards (MCP, A2A); design how these systems collaborate.
  • Enable Conversational & Background Agents - Use Agentforce Studio and Agent Builder to configure chat and background agents; integrate with external channels including voice via hyperscaler APIs.
  • Drive Prompt Engineering & Lifecycle Strategy - Lead prompt design, testing, monitoring, and iteration; define agent lifecycle best practices from development through refinement.
  • Build Hands-On Demos & Prototypes - Co-create quick prototypes.
  • Lead Pre-Sales Workshops - Facilitate whiteboarding, deep dive sessions, and quick enablement for customers and internal teams.
  • Advise on Data & Integration - Integrate Data Cloud (D360), CRM, MuleSoft APIs, and external agent endpoints ensuring cohesive architectures that align with compliance and governance policies.
  • Support Early Adoption - Occasionally assist in proof of value engagements post-sale by tuning agents and guiding customers toward self-sufficient enablement.
  • Own Technical Architecture Decisions - Oversee data modeling, identity resolution, real-time vs. batch patterns, data graph design, and activation strategies within D360.
  • Own Technical Enablement - Create and manage accessible technical documentation, knowledge bases, and FAQ resources to rapidly resolve internal technical inquiries, empowering specialist teams to handle technical discussions confidently.

Required Qualifications

  • Technical Pre-Sales/Consulting - 7+ years of hands-on experience designing and delivering data, analytics, and AI architectures in enterprise environments.
  • Salesforce Expertise - Hands-on experience with Salesforce Agentforce and deep fluency with D360 and core Salesforce platform services.
  • External Ecosystem Knowledge - Strong understanding of external agent ecosystems and interoperability.
  • Proven Track Record - Experience in prompt engineering, agent lifecycle management, and hands-on prototype development.
  • AI & ML Expertise - Experience with machine learning concepts (predictive and generative AI), plus the ability to communicate value to diverse audiences.
  • Data Stack Knowledge - Deep expertise in modern cloud data platforms (Snowflake, Databricks, BigQuery, Redshift) and data ingestion patterns (batch, streaming, CDC).
  • Hands-On Development - Proficiency in programming (e.g., JavaScript, Python, SQL, R) and data frameworks like pandas or Jupyter.
  • Excellent Communication - Strong presentation skills; adept at explaining complex ideas and guiding stakeholders toward impactful solutions.
  • Curiosity & Continuous Learning - Passion for exploring new AI frameworks, sharing insights, and experimenting with cutting-edge technologies.
  • Education - BS in Computer Science, Engineering, Data Science, or equivalent technical field.

Preferred Qualifications

  • Advanced Integration - Experience integrating Salesforce with external agents via APIs and open standards (MCP, A2A).
  • Governance & Observability - Familiarity with prompt governance, observability, and monitoring frameworks.
  • Cross Platform Background - Background in cross-platform integrations (e.g., Hyperscaler SDKs to Salesforce Flows).
  • Multimodal Pipelines - Prior exposure to conversational voice pipelines or multimodal integrations via hyperscaler services.
  • Advanced AI/ML Frameworks - Exposure to frameworks (TensorFlow, PyTorch), MLOps practices, and cloud AI platforms like Google Vertex AI or AWS Sagemaker.
  • Education - BS in Computer Science, Engineering, Data Science, or equivalent technical field.

Lead/Principal Data and AI Architect employer: B Capital

As a Lead/Principal Data and AI Architect, you will thrive in a dynamic work environment that champions innovation and collaboration. Our company offers a robust benefits package, a culture of continuous learning, and ample opportunities for professional growth, all while being at the forefront of cutting-edge AI and data technologies. Located in a vibrant tech hub, we provide a unique chance to work alongside industry leaders and contribute to transformative projects that make a real impact.

B Capital

Contact Details:

B Capital Recruitment Team

StudySmarter Expert Advice🤫

We think this is how you could land Lead/Principal Data and AI Architect

Get Involved in Data Science Meetups

Tap into local data science meetups or workshops to connect with fellow enthusiasts and professionals. These events are goldmines for networking, and sometimes even lead directly to job openings at companies like B Capital!

Show Off Your Projects

Start building a public portfolio showcasing your data science projects on platforms like GitHub or personal websites. Highlight unique analyses or models you've developed. This not only demonstrates your skills but also gets your name out there for roles like Lead/Principal Data and AI Architect at B Capital.

Leverage Professional Networks

Join professional bodies related to data science, like the Data Science Society or similar organisations. Getting involved can lead to mentorship opportunities and insider knowledge about full-time positions at companies like B Capital.

Apply Directly through Our Website

When you find a suitable opening like Lead/Principal Data and AI Architect at B Capital, make sure to apply directly through our website. It gives you an edge and shows you're keen to join our team. Plus, who doesn’t love a direct application? It’s easier than navigating through job boards!

We think you need these skills to ace Lead/Principal Data and AI Architect

Data Architecture Design
AI Solutions Development
Salesforce D360 Expertise
Agentforce Platform Knowledge
Prompt Engineering
Data Cloud Integration
External Agent Interoperability

Some tips for your application 🫡

Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!

Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!

Craft a Tailored Cover Letter:For a full-time role at B Capital, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.

Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at B Capital. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!

How to prepare for a job interview at B Capital

Brush Up on Your Statistics

For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!

Showcase Your Projects

Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!

Get Comfortable with Python and R

Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at B Capital!

Prepare for Case Studies

Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.