At a Glance
- Tasks: Design and build AI solutions that transform commercial processes and drive growth.
- Company: Join a leading LegalTech scale-up with a collaborative and innovative culture.
- Benefits: Competitive salary, 25 days holiday, early finish Fridays, and personal development budget.
- Other info: Diverse and inclusive workplace with opportunities for accelerated career progression.
- Why this job: Be at the forefront of AI technology and make a real impact in a dynamic environment.
- Qualifications: 4+ years in AI/ML Engineering or related fields, with strong communication skills.
The predicted salary is between 70000 - 90000 £ per year.
Key Responsibilities
The AI Architect is a strategic technical partner to the commercial leadership team, responsible for building AI‑powered infrastructure that drives predictable, scalable revenue growth. You will combine advanced engineering with commercial analytics, creating intelligent systems that automate workflows, surface insights and enhance decision‑making across Sales, Marketing and Customer Success. This is a hands‑on, technical role for someone who enjoys building production systems, deploying models and solving real business problems with AI.
You’ll be responsible for both AI engineering (LLMs, ML models, intelligent automation) and foundational commercial analytics, ensuring the business has robust data infrastructure alongside intelligent capabilities that provide genuine competitive advantage. You will own commercial analytics and the technical architecture of our commercial data ecosystem, whilst building AI solutions that transform how teams operate. A core expectation is to champion an AI‑first approach: using AI and automation not just to make existing processes more efficient, but to help the organisation re‑imagine how we work.
- AI Engineering & Intelligent Automation
- Design, build and deploy production AI solutions that drive commercial efficiency and unlock new capabilities for GTM teams.
- Develop and maintain machine learning models for revenue forecasting, pipeline prediction, lead scoring, churn risk and expansion opportunity identification.
- Build intelligent automation using LLMs and AI agents to streamline commercial processes (deal analysis, customer sentiment analysis, competitive intelligence, automated reporting).
- Create AI‑enhanced analytics capabilities that surface patterns, anomalies and opportunities that traditional methods would miss.
- Prototype and ship AI‑enabled workflows rapidly, using tools like Claude, coding assistants and modern AI platforms.
- Evaluate and integrate emerging AI tools, establishing best practices for responsible AI deployment across commercial teams.
- Partner with Sales, Marketing and Customer Success to identify high‑impact opportunities for AI‑driven improvement.
- Revenue Analytics & Insight
- Deliver clean, reliable data and analysis on NRR, GRR, logo retention, expansion and churn, enabling commercial leaders to turn metrics into actionable strategy.
- Build sophisticated analytics combining traditional methods and ML approaches to surface leading indicators and inform proactive decision‑making.
- Translate complex datasets into clear narratives, dashboards and recommendations for senior stakeholders and the board.
- Commercial Systems & Data Infrastructure
- Own the technical architecture of the commercial data ecosystem, ensuring clean data flow between Salesforce, marketing platforms, product analytics and data warehouses.
- Act as commercial data and systems owner: define data models, governance, definitions and quality standards.
- Drive Salesforce technical excellence where needed: build custom objects, fields, automation and integrations that reflect business logic.
- Build and maintain executive‑level dashboards (e.g. in QuickSight or similar) combining traditional metrics with AI‑generated insights.
- Ensure seamless integration between product telemetry, CRM data and commercial analytics systems.
- Stakeholder Management & Technical Leadership
- Operate as a trusted advisor to the COO, CCO and commercial leadership on AI capabilities and data‑driven strategy.
- Work closely with leaders such as the VP Sales, VP Customer and VP Marketing to understand their questions, then design AI tools and analysis that answer them.
- Communicate complex technical concepts clearly to non‑technical stakeholders; frame problems and recommend solutions with clarity.
- Build strong cross‑functional relationships with Finance and Commercial teams, influencing without authority.
- Support onboarding and enablement of commercial team members on AI‑powered tools, dashboards and new ways of working.
- Establish responsible AI practices, addressing bias, explainability and ethical considerations in commercial AI applications.
Requirements
Essential
- 4+ years in AI/ML Engineering, Data Science, Software Engineering or Commercial Analytics with demonstrated AI application development.
- Proven ability to work with LLMs and AI agents (OpenAI, Anthropic, open‑source models) to build practical business applications.
- Familiarity with prompt engineering, RAG (retrieval‑augmented generation) architectures and fine‑tuning approaches.
- Confident working with APIs, databases and modern data stacks, comfortable learning new tools quickly.
- Comfortable working with product usage and adoption data.
- Ability to translate business problems into technical solutions and measure impact on commercial outcomes.
- Excellent communication skills: comfortable presenting to C‑suite and translating technical work into business value.
- Pragmatic builder: bias for shipping working solutions over perfect architectures.
Desirable
- Experience working with CRM systems and commercial datasets (Salesforce experience highly desirable).
- Experience with sales engagement and email marketing platforms (Outreach, Salesloft, HubSpot).
- Background in Revenue Operations, Commercial Analytics or SaaS growth analytics.
- Experience with BI tools (Tableau, Looker, Power BI) and AWS QuickSight.
- Understanding of causal inference methods for measuring intervention impact.
- Experience in legal tech, professional services software or complex B2B sales environments.
- Track record of building internal tools or platforms used by non‑technical teams.
Benefits
What we offer you
- Competitive salary (depending on experience).
- 25 days holiday per year (plus public holidays).
- Early Finish Fridays - on the last Friday of every month, we finish at lunchtime!
- Pension with NEST.
- Personal Learning & Development budget.
- Enhanced parental leave policies so you can spend more time with your family.
- Lots of opportunities for accelerated professional development and career progression.
- Work alongside a supportive and talented team with the opportunity to grow one of the world's leading LegalTech scale‑ups.
- A warm, genuinely collaborative culture and an awesome team; and Regular socials.
Power in diversity
We put users at the heart of our design to provide legal transaction experiences that everyone loves. In order to make that a reality, we seek to foster a diverse and inclusive working environment that can empower our people to be creative, effective and innovative, to build a brand we are proud of. We don't discriminate against gender, race, religion or belief, disability, age, marital status or sexual orientation. Whatever your background may be, we welcome anyone with talent, drive and emotional intelligence. We're committed to building a diverse team, and are constantly looking for ways to improve our processes to help us do that.
AI Architect employer: Legatics Limited
As an AI Architect at our innovative LegalTech scale-up, you'll thrive in a dynamic and collaborative environment that champions an AI-first approach to transform commercial operations. We offer competitive salaries, generous holiday allowances, and a strong focus on personal development, ensuring you have the resources to grow your career while working alongside a talented team dedicated to fostering diversity and inclusion. With early finish Fridays and regular social events, we create a supportive culture where your contributions are valued and impactful.
StudySmarter Expert Advice🤫
We think this is how you could land 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 Legatics Limited!
✨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 AI Architect at Legatics Limited.
✨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 Legatics Limited.
✨Apply Directly through Our Website
When you find a suitable opening like AI Architect at Legatics Limited, 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 AI Architect
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 Legatics Limited, 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 Legatics Limited. 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 Legatics Limited
✨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 Legatics Limited!
✨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.