Development Manager, AI Transformation & Innovation

This is a high-impact role with a mandate to change how Quest builds software, operates as a business, and innovates its product portfolio. You will lead a team of ten software engineers, data scientists and data engineers across three connected areas: AI-first software development: Roll out and continuously improve an AI-first development lifecycle (AI-DLC) across Quest Engineering.

About Quest

• Build and validate AI-driven prototypes that can differentiate Quest and be adopted across the product portfolio.
• The team will have scope to grow as it demonstrates impact, creating an opportunity for the role to expand significantly.
• Develops technically strong people and enjoys building high-performing teams.
• Is ambitious for impact and earns increased scope through results.
• Why Quest Software… Quest Software helps organisations around the world manage and secure their data & IT environments and get more value from them.
• This role sits at the centre of how Quest is changing — the way we build software, the way we run the business, and the innovations that will differentiate our products.
• It starts with a team of ten and a broad mandate, and it grows on the strength of what you deliver.

Responsibilities

• Lead data science and engineering initiatives with the CIO, Finance and other functions to automate processes and turn Quest’s data into actionable insight.
• Responsibilities 1) AI-first software development Lead the design, rollout and adoption of AI-DLC across Quest Engineering, working with development leaders across locations and portfolios.
• Drive adoption through practical workflows, playbooks, onboarding, champions and hands-on support.
• Establish responsible-use guardrails covering quality, security, licensing, IP and data.
• Continuously evolve the approach as AI models and tooling develop.
• AI consumption and budget, including monitoring, model selection, routing and cost controls.
• Measure and report engineering productivity and team health using metrics such as throughput, cycle time, quality, defects and engineer experience.
• Build a high-performance team with clear accountability and a strong reputation across engineering.
• Data science and business transformation Own a roadmap of AI and automation initiatives across the business, prioritising opportunities based on value and capacity.
• Partner with the CIO, Finance, Sales, Marketing, Customer Success and Product to identify and deliver high-value use cases.
• Turn Quest’s existing data into commercially useful insight, including initiatives such as customer churn and propensity modelling.
• Build the data engineering foundations required to scale this work, including pipelines, data quality, governance and access.
• Ensure models and insights influence real business decisions rather than becoming standalone analyses or dashboards.
• Manage privacy, security and compliance considerations in partnership with the relevant functions.
• Innovation Lead a small, fast-moving prototyping capability focused on commercially meaningful innovation.
• Identify, prototype and validate AI use cases for the Quest product portfolio.
• Prioritise reusable capabilities that can benefit multiple products.
• Work with Product and Architecture to create a clear path from successful prototype to product adoption.
• Stop initiatives that do not demonstrate sufficient value and continuously monitor the external technology and competitive landscape.
• Trusted data demonstrates the health and productivity of engineering teams and identifies measurable improvement.
• A prioritised roadmap is in place and initial initiatives are delivering measurable value.
• Data-driven insights, including churn propensity, are being used to influence business decisions.

Requirements

• Essential Experience leading a team of 8–10 software developers using an AI-first development methodology.
• 5–8 years’ experience as a first-line manager.
• Degree in Computer Science or a related discipline.
• Strong technical credibility across software engineering and/or data science.
• Experience working with multiple stakeholders across a business.
• Track record of building and leading high-performing teams.
• Excellent written and verbal communication, including presenting to senior leadership and non-technical audiences.
• AI consumption is visible, understood and managed within budget.
• At least one prototype has been successfully adopted by a product team, ideally across multiple products.
• The team is high-performing, accountable and well regarded, with a clear case for growth.
• Leadership attributes We are looking for someone who: Is comfortable operating in ambiguity and shaping the role through execution.
• Uses evidence to make decisions and changes course when the data demands it.
• Prioritises ruthlessly and is comfortable saying no.

Preferred

• Experience managing or working closely with data scientists and data engineers.
• Understanding of AI development economics, including token consumption, model selection and cost management.
• Experience with engineering productivity metrics such as DORA.
• Experience delivering machine learning or data science solutions into production.
• Experience with enterprise data platforms, pipelines and governance.
• Experience leading organisational change without direct authority.
• Enterprise software or B2B SaaS experience.
• Experience building and scaling a team from a small starting point.
• What success looks like in the first 12 months AI-DLC: Adopted beyond the pilot, with repeatable enablement for new teams.

Influences effectively without direct authority. Is commercially minded and treats budget and AI consumption with discipline.