Software Project Manager

Join our growing team and become part of a close-knit, welcoming group of world-class innovators, who are passionate about building products that make a real difference.

Our team thrives on solving complex technical challenges and has a long history of delivering world-first cybersecurity solutions. With experience spanning Silicon Valley startups and large-scale multi-national corporations, our team offers an exceptional environment for mentoring, learning, and growth.

This spirit of innovation extends beyond our own walls: we maintain strong ties with Belfast's leading universities through collaborative research projects, and are now launching new initiatives in AI, networking, and encryption.

Our 100+ staff worldwide describe Arqit as providing a positive and inclusive working environment, where staff feel that managers care about the success and well-being of their teams, and individuals feel valued as employees.

As we continue to grow and innovate, we have a new opportunity for a software project manager to run a portfolio of software projects across our engineering teams. The work spans a range of technologies, with a particular focus on Python, Rust and Java/Kotlin. Some projects are AI-focused, so you'll need to be comfortable managing work where requirements are still forming and the technology is moving quickly.

You'll be the person who keeps projects on track, clear and delivered. You'll work closely with engineers, product, security, sales and pre-sales, and you'll be the one who turns a customer need and a set of product requirements into a workable plan that a team can deliver against.

What you'll be doing

• Work with the product lead and engineering managers to plan, run and report on multiple concurrent software projects from kick-off to delivery. • Build and maintain project plans, timelines, dependencies, budgets and resourcing – and help the team manage through changes, delays and the inevitable curve-balls of product development. • Identify, log and manage risks, issues and dependencies, and escalate early. • Work with engineering leads to scope work, estimate effort and agree what gets done first. • Help the engineering team with accurate, low-impact metric gathering to identify where and how resources are used. • Manage the AI project pipeline: scoping experiments, setting success criteria, tracking model and data dependencies, and managing the move from prototype to production. • Ensure projects meet security and compliance requirements, including data classification, export control and customer security questionnaires. • Keep stakeholders informed with clear, honest status updates • Champion good delivery practice: definition of done, code review, testing, documentation and post-project reviews – in a rapidly-changing environment where AI forms an increasingly important tool for the development teams. • Support prioritisation across the portfolio and help leadership make trade-offs with real information.