Hardware AI Engineer

We are the PE AI team, and we focus on improving engineering productivity through smart technology. We work across hardware and software projects, partnering with teams to embed AI into their workflows., * Contribute hands-on toward the development of AI-based solutions for Hardware Verification automation.

• Curate/develop solutions based on OpenAI Codex skills and tool integrations (e.g., simulation flows, log analysis, code review/refactor support).
• Collaborate with Arm Engineering teams to capture real engineering struggles and turn them into clear requirements.
• Build quick prototypes and evaluate EDA AI tools, to validate feasibility and quantify impact.
• Drive adoption as a change leader: run demos/workshops; Contribute onboarding guides; Identify and remove adoption blockers., * Arm Hardware engineers can point to real workflow time saved (cycle time, debug time, triage effort) and product quality improvements (number of bugs found, PPA improvements) with credible evidence.
• Prototypes rapidly prove value or stop quickly with clear learning.
• Teams onboard quickly and stick with it: adoption grows because friction is removed and value is obvious., Arm’s approach to hybrid working is designed to create a working environment that supports both high performance and personal wellbeing. We believe in bringing people together face to face to enable us to work at pace, whilst recognizing the value of flexibility. Within that framework, we empower groups/teams to determine their own hybrid working patterns, depending on the work and the team’s needs. Details of what this means for each role will be shared upon application. In some cases, the flexibility we can offer is limited by local legal, regulatory, tax, or other considerations, and where this is the case, we will collaborate with you to find the best solution. Please talk to us to find out more about what this could look like for you.

• Hands on experience with design verification methodology: Deep understanding of RTL design, interfaces between RTL, testbench and Verification IP, experience with debugging compile and simulation issues.
• Experience with EDA vendor tooling: Domain knowledge of at least one (of the three major) EDA vendor toolset.
• AI tooling fluency: Practical experience using AI for engineering automation (prompt design/iteration, structured outputs, tool use).
• Strong solving attitude: you can quickly diagnose why something doesn’t work in a real environment and drive resolution across teams.
• Clear written communication: can turn ambiguous conversations into requirements and actionable plans.

“Nice To Have” Skills and Experience:

• Automation / scripting: Strong in at least one scripting language (Python preferred). Ability to integrate and orchestrate tools (parsing logs/reports, running flows, collecting results).
• Experience in an Application Engineer / internal customer-facing role where you translated user needs into working solutions.
• Familiarity with agentic workflows, skills, tool calling patterns

£97,300

• £131,700

per year