Senior AI Engineer - Perm Developer Productivity

SRG; Manchester; Hybride; GBP 100 000 - 110 000; Plein temps

Avantages offerts par ce poste

Bonus

Hybrid work in Manchester

Résumé du poste

SRG in Manchester is hiring a Lead AI Engineer for Developer Productivity to drive AI-enabled engineering tooling and workflows in real codebases.

The role is hands-on and requires building with LLM APIs, observability, CI/CD, and Git-based integrations, with a pragmatic, evidence-driven mindset.

The position is permanent, hybrid (2 days in-office), offering a salary of £100,000–£110,000 plus a bonus and benefits.

Qualifications

• Strong professional software engineering experience, including building and operating production software.
• Excellent programming and software design skills, with a solid grasp of testing, CI/CD and code review.
• Hands-on experience building with LLM APIs, including tool calling and agentic workflows.
• Day-to-day use of AI coding tools and agents on real codebases, with an evidence-based view of where they help and where they hurt.
• A practical understanding of how LLMs and agents fail: plausible but wrong code, fixes that mask symptoms, tests gamed to pass, context limits and cost growth.
• Experience integrating with Git platforms, CI/CD, issue trackers and observability tooling.
• Experience designing evaluations for AI outputs, or comparable experimental rigour.
• Python (or similar) and SQL for preparing code, documents and tickets for retrieval.
• Credibility with engineers and the ability to influence without line authority, including winning over sceptics.
• Helpful: Bitbucket, Jenkins/Harness, Docker, Kubernetes, AWS, FastAPI, DORA-style measurement, RAG and vector search, self-hosted open-weight models, or a regulated environment such as gambling or financial services

Responsabilités

• Lead the hands-on work of building tooling and workflows to integrate AI into real codebases.
• Measure results with evidence-based evaluations and observable metrics to guide decisions.

Connaissances

Software engineering

LLM APIs

Python

SQL

CI/CD

Code reviews

Evidence-based evaluation

Influencing without authority

Observability

Retrieval augmented generation

Outils

Docker

Kubernetes

AWS

Git platforms

Jenkins/Harness

FastAPI

Vector search

Self-hosted models

Description du poste

Lead AI Engineer - Developer Productivity

Manchester (hybrid, 2 days a week in the office) | Permanent | £100,000-£110,000 + bonus

A leading digital and retail business in the global betting and gaming industry is looking for an engineer who'd rather prove what works than sell what's fashionable.

With around 250 engineers building and running its platforms, the business wants to use LLMs and coding agents to help them deliver better software, faster, and to be able to show the evidence. This is a hands‑on role. You'll work out where AI helps engineers and where it doesn't, build the tooling and workflows that make it work in real codebases, and measure the results honestly. You'll use the best available models, coding agents and open-source tools. This isn't a model‑building or research role.

What they're looking for:

• Strong professional software engineering experience, including building and operating production software
• Excellent programming and software design skills, with a solid grasp of testing, CI/CD and code review
• Hands‑on experience building with LLM APIs, including tool calling and agentic workflows
• Day-to-day use of AI coding tools and agents on real codebases, with an evidence-based view of where they help and where they hurt
• A practical understanding of how LLMs and agents fail: plausible but wrong code, fixes that mask symptoms, tests gamed to pass, context limits and cost growth
• Experience integrating with Git platforms, CI/CD, issue trackers and observability tooling
• Experience designing evaluations for AI outputs, or comparable experimental rigour
• Python (or similar) and SQL for preparing code, documents and tickets for retrieval
• Credibility with engineers and the ability to influence without line authority, including winning over sceptics
• Helpful: Bitbucket, Jenkins/Harness, Docker, Kubernetes, AWS, FastAPI, MCP, DORA-style measurement, RAG and vector search, self-hosted open-weight models, or a regulated environment such as gambling or financial services