Senior Software Engineer (Python)

TL;DR

Senior Software Engineer (Python): Building and optimizing the IP Lifecycle Management (IPLM) suite, including a Python CLI client and caching layer, with an accent on systems engineering and AI-assisted development. Focus on designing user-facing commands, integrating version control systems, and productionizing agent-based QA and implementation workflows.

Location: Hybrid in Bracknell, UK

Company

hirify.global provides tools for managing intellectual property, releases, and dependencies at scale for semiconductor and hardware design teams.

What you will do

• Design and implement user-facing pi CLI commands for IP, workspace, release, update, and snapshot workflows.
• Extend the data-management layer by integrating with Perforce, SVN, and Git-based version control systems.
• Diagnose and fix regressions in the CLI's integration and unit test frameworks to ensure releasable branches.
• Prototype and productionize AI-assisted development workflows and agent-based QA loops.
• Collaborate with server teams and support teams to resolve complex customer errors.

Requirements

• 5+ years of professional software engineering experience with strong daily Python proficiency.
• Experience with command-line tooling: argument parsing, subcommand design, and JSON output.
• Proficiency with version control systems, specifically Perforce and Git.
• Solid grasp of writing and maintaining unit and integration test frameworks.
• Comfort working in Linux environments, including bash scripting and system diagnostics.
• Clear written communication for documenting design decisions and patch rationale.

Nice to have

• Experience building Python CLIs used by other engineers.
• Exposure to IP lifecycle management, EDA tooling, or the semiconductor domain.
• Experience with Microsoft Windows development and packaging.
• Hands-on use of AI-assisted tools like Claude Code, Copilot, or Cursor.
• Background in Rust or interest in ML and applied deep learning.

Culture & Benefits

• Hybrid workplace model.
• Integration of modern AI-assisted development practices into the daily workflow.
• Emphasis on AI fluency and adherence to responsible AI governance and security standards.