Manager, Software Engineering

Job description

**About SugarAI UK Limited** SugarAI is redefining CRM for the age of AI. We’re delivering on the original promise of CRM—turning fragmented customer and revenue signals into clear, prioritized action. Instead of more dashboards or surface-level insights, we help teams focus on what matters most and know exactly what to do next. More than two decades after our founding, we’re entering a new chapter with clarity and momentum—building intelligent, intuitive solutions that work within the flow of how teams actually sell and serve. We’re focused on solving complex, real-world challenges where relationships, context, and precision make all the difference. Our global team is united by a shared commitment to impact, ownership, and continuous growth. We create an environment where thoughtful ideas move quickly, where people are trusted to lead, and where flexibility supports how great work gets done. If you’re excited to help shape what’s next in AI-driven CRM—and build technology that drives real outcomes—we’d love to meet you. ### Impact You Will Make in the Role (Key Responsibilities): - Lead, coach, and develop a team of software engineers through structured 1:1s, career development planning, performance feedback, and clearly set expectations, owning the full people management cycle including goal-setting, reviews, promotions, and compensation conversations. - Rebuild team culture from the ground up, establishing psychological safety, accountability, and a genuine appetite for continuous improvement, identifying root causes of underperformance rather than addressing symptoms. - Own delivery by introducing and maintaining effective operating rhythms, removing blockers systematically, and bringing rigour to planning and sprint health using metrics including velocity, cycle time, throughput, and defect rates. - Be the technical conscience of the team, setting and enforcing engineering standards across code quality, testing, reliability, and maintainability, reducing technical debt strategically, and providing hands-on technical guidance. - Lead the adoption of AI-first ways of working, introducing generative AI tooling into the engineering workflow and helping engineers understand and embrace their role as orchestrators in a spec-driven development environment. - Develop multidisciplinary engineers by actively breaking down silos between front end, back end, data, and QA, building development plans that broaden capability and reduce single points of failure across the team. - Partner with product and wider stakeholders to align engineering delivery with business priorities, communicating progress, risks, and trade-offs clearly and ensuring engineering has a credible voice in strategic conversations. ### What You Will Bring (Qualifications/Experience): - 5+ years of direct engineering management experience with a track record of developing individuals, managing performance, hiring talent, and building high-functioning teams. - Proven experience leading a team through a period of significant change, whether through a merger and acquisition, organisational restructure, or a turnaround from low morale and underperformance. - Strong technical credibility with a background in software development, sufficient to guide architectural decisions, set engineering standards, and earn the genuine respect of the engineers you manage. - A clear and well-formed point of view on the future of software engineering, including AI-first development, spec-driven workflows, and the evolving role of the engineer. - Fluency in engineering metrics and delivery operations, with a clear understanding of the relationship between capacity, velocity, and throughput and the ability to use data to drive decisions. - Strong communication across audiences, able to hold a room of engineers and a room of senior stakeholders with equal confidence, translating between technical complexity and business context. ### Preferred Qualifications/Experience: - Experience in post-merger or post-acquisition engineering environments where you have rebuilt culture and operating practice from a difficult starting point. - A demonstrated track record of moving teams from siloed, specialist working towards cross-functional, multidisciplinary delivery. - Measurable outcomes in team health, delivery predictability, or engineering effectiveness, with the data to support them. - Experience introducing generative AI tooling into an engineering team and navigating the human side of that change alongside the technical implementation.