Arqit - Software Project Manager
Requirements
• History of successful project or delivery management on software projects. • A working understanding of software development projects, and experience communicating positively and constructively with stakeholders including product and engineering management, software developers and testers, and customers. You don't need to write code, but you need to understand what the engineers are telling you and ask the right questions. • Strong written and verbal communication, with the ability to explain technical trade-offs to non-technical audiences. • Proven ability to manage several projects at once, with competing priorities and multiple stakeholders. • Please note that ability to work in the UK without visa restrictions is ESSENTIAL • Useful to have (but not essential) • Experience managing AI or machine learning projects • Experience in cybersecurity, cryptography, defence, government or other regulated environments. • Familiarity with security and compliance frameworks, such as ISO 27001, Cyber Essentials or similar.
Responsibilities
• What you'll be doin • 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.
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