Lead AI Engineer (Enterprise Data & AI)

Climate17; Remote; GBP 55,000 - 65,000; Full time

Job summary

A leading sustainability technology company is searching for a Lead AI Engineer to deliver enterprise-grade AI solutions. This remote-first role involves designing AI agents and workflows, utilizing Microsoft's AI ecosystem. The ideal candidate should have strong experience with enterprise data platforms and practical expertise in deploying AI solutions. Responsibilities include integrating AI with enterprise systems and ensuring data quality. Interested candidates should apply by sending their CV to Kris Kobi at the provided email.

Qualifications

• Strong hands-on experience with enterprise data platforms.
• Practical experience building or deploying AI / LLM-based solutions.
• Strong Python and SQL skills required.

Responsibilities

• Design and deploy AI agents using Microsoft's AI ecosystem.
• Develop RAG-style AI solutions with proprietary data.
• Integrate AI solutions with enterprise platforms.
• Implement monitoring practices around cost and model behaviour.

Skills

Python

SQL

Enterprise data platforms

AI and LLM-based solutions

Data modelling

Tools

Databricks

Azure/Fabric

Job description

Job Title: Lead AI Engineer (Enterprise Data & AI)

Location: UK (Remote-first with occasional site visits)

Salary: Up to £65,000 benefits

Working Pattern: Full-time, permanent

Overview

We are seeking a hands-on Lead AI Engineer to deliver enterprise-grade AI solutions that move from concept to production. This role focuses on building AI agents, conversational interfaces, and retrieval-augmented systems that sit on top of trusted enterprise data. You will work closely with business stakeholders to translate real operational needs into deployed AI products, with a strong emphasis on data quality, semantic modelling, and governance.

Key Responsibilities

• Design, build, and deploy AI agents and workflows using Microsoft’s AI and data ecosystem
• Develop RAG-style AI solutions enabling LLMs to reason over proprietary enterprise data
• Own and curate semantic models that ensure AI outputs are accurate, explainable, and business-friendly
• Integrate AI solutions with enterprise platforms via APIs and automation tools
• Partner with non-technical stakeholders to prototype, test, and operationalise AI use cases
• Implement monitoring and governance practices around cost, performance, and model behaviour

Required Experience

• Strong hands-on experience with enterprise data platforms (e.g. Databricks, Azure/Fabric)
• Practical experience building or deploying AI / LLM-based solutions (including RAG architectures)
• Strong Python and SQL skills
• Experience designing analytics or semantic data models
• Ability to explain complex technical concepts to business users

Desirable

• Experience with Microsoft Copilot, Power Platform, or similar low-code AI tooling
• Exposure to AI governance, monitoring, or LLMOps practices
• Background in data engineering, analytics engineering, or applied AI

Profile

This role suits someone who enjoys building real systems, cares deeply about data accuracy, and is motivated by delivering tangible business value rather than research alone.

How to apply

If this sounds like a role for you, kindly send your cv to Kris Kobi at [e-mail]