Software Delivery & QA Manager - Generative AI

Manchester

2 days ago

Create job alert

Join an award-winning, internationally recognised organisation as a Software Delivery & QA Manager, leading the structured delivery and quality governance of Generative AI solutions powering next-generation legal, finance, and HR intelligence. You will take ownership of delivery execution, AI model evaluation, and release oversight for cutting-edge AI products operating at scale.

This role sits at the intersection of engineering execution, AI model evaluation, and release governance. You'll ensure every AI release is dependable, rigorously evaluated, and drives an exceptional, next-generation experience for users.

Reporting to the Director of Generative AI, you'll combine disciplined delivery leadership with QA oversight and AI performance evaluation, translating strategy into coordinated execution and turning metrics into clear, structured release decisions. The role will focus upon:

Lead end-to-end delivery cycles for Generative AI initiatives, from planning through deployment and iteration.
Own release cadence, milestones, dependencies, and cross-team alignment in engineering-led environments.
Oversee QA and AI model evaluation to ensure outputs meet standards for accuracy, robustness, and reliability.
Interpret performance metrics and evaluation results to assess release readiness.
Maintain dashboards, define KPIs and thresholds, and use SQL or equivalent BI tools to validate insights.
Translate quality and performance signals into structured go/no-go recommendations and clear stakeholder reporting.
Ensure releases are controlled, evidence-based, and aligned with regulatory expectations where required.Required Experience

Demonstrable end-to-end delivery ownership in engineering-led environments, with direct accountability for releases and deployment cycles.
Proven ability to define release readiness, manage delivery risks, and coordinate cross-functional stakeholders.
Strong QA and AI evaluation experience, with the ability to translate metrics into actionable decisions.
Advanced data fluency, including SQL, BI tools, dashboards, or statistical analysis.This is a rare opportunity to take ownership of delivery and AI quality governance across a fast-scaling suite of generative AI products used by real customers at scale. You'll work directly with senior AI and engineering leaders, influencing how performance, evaluation, and release decisions are defined at a strategic level. For the right individual, this represents an exceptional career move - combining high visibility, meaningful ownership, and long-term impact within a market-leading organisation investing heavily in AI innovation.

INDAMS

Portfolio Payroll Ltd is acting as an Employment Agency in relation to this vacancy

Related Jobs

View all jobs

Head of Engineering

SMART Systems Technician

Senior Developer - AI Operations (Python/Golang)

Software Engineer

Platform Engineer

DevSecOps Engineer

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Feb 10, 2026

Careers

How Many Edge Computing Tools Do You Need to Know to Get an Edge Computing Job?

If you’re trying to start or grow a career in edge computing, it can feel like you’re navigating a maze of tools, frameworks and platforms — Kubernetes, Docker, IoT frameworks, AWS Greengrass, Azure IoT Edge, OpenShift, TinyML toolkits, networking orchestration, real-time streaming frameworks, and on it goes. Scroll job boards and community forums and it’s easy to conclude that unless you master every buzzword imaginable, you’ll never get a job. Here’s the honest truth most edge computing hiring managers won’t necessarily say out loud: 👉 They don’t hire you because you know every edge computing tool — they hire you because you can solve real system problems using the tools you know. Tools matter, yes — but only when they support clear outcomes: reliable systems, performance at scale, secure edge deployments and real business value. So how many edge computing tools do you actually need to know to secure a job? For most edge computing roles, the answer is fewer than you think — and a lot clearer when sorted by fundamentals and roles. This guide shows you what matters, what doesn’t, and how to focus your time wisely so you come across as capable, confident and employable.

Feb 3, 2026

Jobs

What Hiring Managers Look for First in Edge Computing Job Applications (UK Guide)

In today’s fast-evolving tech landscape, edge computing is one of the most sought-after fields — blending distributed systems, embedded systems, networking, cloud, IoT, data and real-time processing. But that also means hiring managers are highly selective. They scan applications fast and look for signals of relevance, impact, technical depth and real-world delivery long before they read every line. This guide demystifies what hiring managers in edge computing look for first in your application — so you can tailor your CV, portfolio and cover letter to jump out of the stack. Whether you’re targeting edge systems roles, embedded IoT edge jobs, edge-native data roles, edge platform engineering or edge-AI positions, this checklist will help you position your experience in a way hiring managers can trust immediately.

Jan 23, 2026

Education

The Skills Gap in Edge Computing Jobs: What Universities Aren’t Teaching

Edge computing is rapidly moving from niche concept to critical infrastructure. As organisations deploy connected devices, sensors, autonomous systems and real-time analytics, processing data closer to where it is generated has become essential. From smart cities and manufacturing to healthcare, transport, defence and telecommunications, edge computing underpins systems where latency, reliability and resilience matter. Demand for edge computing skills across the UK is rising steadily — yet employers consistently report difficulty finding candidates who are genuinely job-ready. Despite growing interest and academic coverage, universities are not fully preparing graduates for real edge computing jobs. This article explores the edge computing skills gap in depth: what universities teach well, what they consistently miss, why the gap exists, what employers actually want, and how jobseekers can bridge the divide to build sustainable careers in edge computing.