AI Engineer – Commercial

Legatics

AI Engineer developing production AI systems to support commercial teams at a leading LegalTech scale-up. Building LLM-powered applications and ML models for collaboration and deal closure.

Posted 7/16/2026full-timeLondon • 🇬🇧 United KingdomMid-LevelSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in building and deploying AI applications, particularly LLM-powered tools, while effectively translating business problems into technical solutions. Proficient in integrating systems and ensuring data flow across platforms, with a strong focus on responsible AI practices.

Highest-signal resume keywords

AI Application DevelopmentML Model Training and DeploymentAPI IntegrationPrompt EngineeringCommercial Analytics

ATS Keywords

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Hard Skills

PythonMachine LearningLLM ApplicationsSystem DesignData Analysis

Soft Skills

Strong CommunicationProblem-Solving

Tools & Technologies

SalesforceTableauLookerPower BIQuickSight

Industry Keywords

RevOpsCommercial AnalyticsSaaS Growth AnalyticsLegalTechB2B Sales

Tech Stack

Tools & technologies

PythonTableau

About the role

Key responsibilities & impact

Design, build and deploy production AI applications (LLM-powered tools, agents, automation) that commercial teams use daily.
Build and maintain ML models for problems like churn risk, lead scoring, pipeline and revenue forecasting, and expansion signals.
Ship fast: prototype, get it in front of users, iterate. You'll own features end to end, from data to interface.
Integrate systems via APIs so data flows cleanly between our CRM, product analytics and data warehouse.
Work directly with commercial leaders to find the highest-impact problems, then build the tools that solve them.
Set sensible practices for responsible AI (evaluation, monitoring, bias, explainability) as we scale usage.

Requirements

What you’ll need

4+ years building and shipping production software, with recent hands-on work deploying AI/ML or LLM-powered applications. We care about what you've built and run in production, not just prototyped.
Strong general engineering fundamentals: you write clean, maintainable code (Python or similar), work confidently with APIs, databases and modern data stacks, and can reason about system design.
Practical experience building applications on LLMs (OpenAI, Anthropic, open-source), including prompt engineering and RAG architectures.
Experience training, deploying or productionising ML models, and measuring whether they actually work.
Ability to translate a vague business problem into a technical solution and measure its commercial impact.
Strong communication: you can present to non-technical stakeholders and C-suite, and translate technical work into business value.
Bias for shipping working solutions over perfect architectures.
Desirable
Experience with commercial or CRM data (Salesforce especially), or a willingness to own it.
Familiarity with fine-tuning, evaluation frameworks or causal inference for measuring intervention impact.
Experience with BI tools (Tableau, Looker, Power BI, QuickSight) and building dashboards.
Background in RevOps, commercial analytics or SaaS growth analytics.
Experience in LegalTech, professional services software or complex B2B sales environments.
Track record of building internal tools used by non-technical teams.

Benefits

Comp & perks

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.