Senior AI Engineer - Hybrid, Client-Facing & Platform

develop; Greater London; Hybrid; GBP 42,000 - 70,000; Full time

Benefits offered by this job

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Discretionary bonus

Job summary

develop in London is seeking a Senior Data & AI Engineer to join the engineering team and drive platform development and live client delivery. This hands-on role sits at the intersection of AI engineering and customer engagements, with mentorship potential as the team scales.

You will build data pipelines, model data, design QA processes for AI outputs, and collaborate with consultants to translate requirements into reliable solutions for complex, sustainability and investments use cases.

Qualifications

• 4-5 years of professional software or data engineering experience.
• Production experience with Large Language Models, including prompt design and evaluation.
• Experience building and maintaining data pipelines that teams rely on.

Responsibilities

• Build and maintain AI-assisted assessment pipelines that extract and evaluate evidence from company disclosures.
• Design and maintain QA and citation processes around AI outputs.
• Own data models and ingestion pipelines for portfolio and issuer data.
• Develop evaluation frameworks and benchmark pipeline performance.
• Improve reliability of probabilistic AI outputs for production use.
• Work with large datasets and pipelines used by other teams and clients.
• Contribute to backend services and APIs supporting the platform.
• Support deployment, monitoring, and observability across engineering workflows.
• Own technical work end-to-end from design to production.
• Help establish engineering standards, testing practices and development processes.

Skills

Python

Large Language Models

SQL

Data pipelines

Azure or GCP

Job description

develop in London is seeking a Senior Data & AI Engineer to join the engineering team and drive platform development and live client delivery. This hands-on role sits at the intersection of AI engineering and customer engagements, with mentorship potential as the team scales.

You will build data pipelines, model data, design QA processes for AI outputs, and collaborate with consultants to translate requirements into reliable solutions for complex, sustainability and investments use cases.