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Director of Engineering

Job in Manchester, Greater Manchester, M9, England, UK
Listing for: Accelerant
Full Time position
Listed on 2026-02-13
Job specializations:
  • IT/Tech
    IT Project Manager, Cloud Computing, Systems Engineer
Salary/Wage Range or Industry Benchmark: 125000 - 150000 GBP Yearly GBP 125000.00 150000.00 YEAR
Job Description & How to Apply Below

Director of Engineering (Platform Intelligence)

Location: Remote

About the Role

Accelerant is seeking an experienced Director of Engineering to lead one of our full stack engineering teams within the Product & Technology group. This role combines people management with strong project management discipline and Agile practices. You will be responsible for developing engineering talent, managing cross team dependencies, and enabling your team to build high quality, impactful SaaS applications.

Core Responsibilities
  • Team Development & Mentorship: Invest in your team members by promoting continuous growth, offering guidance and support, and fostering a positive and inclusive work environment.
  • Project Planning & Execution: Own end to end project delivery. Define scope, create realistic timelines, identify risks early, break down initiatives into milestones, and track progress against commitments.
  • Agile Process Ownership: Serve as the Agile champion for your team. Ensure consistent execution of Scrum ceremonies, track sprint metrics, and refine processes to improve predictability.
  • Stakeholder & Dependency Management: Build relationships with business stakeholders, Product Management, Design, and partner engineering teams. Communicate status, manage expectations, flag risks early, and coordinate across teams to prevent blockers.
  • Technical Roadmap Ownership: Partner with the team Architect on technical direction and design decisions. Contribute to quarterly planning and OKR definition. Balance technical debt reduction with feature delivery.
  • Engineering & Operational Excellence: Drive engineering best practices and scalable solutions. Own production reliability, lead incident response and post mortems, and improve system stability.
  • AI Tooling & Adoption: Champion the adoption of AI tools and practices within the team. Evaluate and implement AI assisted development tools, establish best practices for AI augmented workflows, and drive measurable improvements in developer productivity.
  • Performance Management: Monitor and guide the performance of your team members, providing regular feedback and helping each individual reach their career potential.
Technical Requirements
  • Full Stack SaaS Understanding: A solid understanding of full stack SaaS applications and best practices is necessary to effectively support and guide teams.
  • API Integration

    Experience:

    Strong experience consuming external APIs and integrating third party services. Understanding of API contracts, versioning, health monitoring, and production readiness requirements.
  • Machine Learning & Data Science Familiarity: Basic understanding of machine learning concepts, model deployment, and inference APIs. Ability to collaborate effectively with Data Science teams on model integration and productionization.
  • Data Platform Familiarity: Familiarity with data pipelines and modern data platforms. Experience with Snowflake, data warehousing concepts, or similar technologies is a plus.
  • Familiarity with the Stack: Familiarity with our stack, which includes Type Script (for both frontend and backend), Svelte, Node.js/Nest.js, AWS, and Infrastructure as Code (IaC), is preferred, though experience with similar technologies is also valuable.
  • Agile Tooling: Proficiency with Agile project management tools such as Jira, including workflow configuration, reporting, and dashboard creation.
Qualifications
  • Experience: 5 to 7 years as an engineering manager, ideally leading full stack teams in a SaaS environment. Track record of delivering complex software projects on time.
  • Agile Expertise: Deep understanding of Agile principles and Scrum methodology. Scrum Master or similar certification is a plus.
  • Cross Team

    Collaboration:

    Proven experience working with data teams, whether Data Science, Data Engineering, or Analytics. Ability to bridge technical discussions across different engineering disciplines.
  • Operational Mindset: Experience owning production systems, leading incident response, and driving reliability improvements. Comfortable with on call responsibilities and production support.
  • Leadership

    Skills:

    Proven track record of effective team leadership, performance management, and fostering a…
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