Python-Driven AI Workflows Engineer

Neural Concept; Cambridge; Hybrid; GBP 70,000 - 100,000; Full time

Benefits offered by this job

Competitive salary

Hybrid work model (up to 2 remote days

Job summary

Neural Concept is seeking an AI Workflows Engineer to design and deliver Python‑first engineering solutions for industry applications, collaborating with the Vertical Solutions Product Manager and customers to define the roadmap.

You will work closely with CAD/CAE specialists to implement, maintain, and evolve these workflows, identify reusable components for the platform, and help accelerate adoption across applications in a hybrid Cambridge-based setting.

Qualifications

• Experience building and shipping production Python tools in fast-moving, cross-functional teams.
• Hands-on Python engineer with strong software practices: packaging, testing (pytest), CI, code review, docs, and git.
• Background in physics or engineering, or equivalent experience.

Responsibilities

• Lead the design and delivery of AI-powered engineering workflows for specific industry applications and integrate them into the Neural Concept platform for scalable adoption.
• Build & integrate: act as primary Python developer - define clean interfaces with CAD/CAE specialists; own coding, testing, CI, packaging, and releases.
• Upstream reusable components to the Neural Concept platform.
• Standardize: turn recurring pains into reusable templates, presets, and best practices.
• Engage reference customers and end users to gather feedback, and drive adoption.
• Help define and review documentation, playbooks and hands-on training sessions.

Skills

Python

Testing (pytest)

CI/CD

Education

Physics or Engineering background

Tools

Python tooling

Git

Software packaging

Job description

Neural Concept is seeking an AI Workflows Engineer to design and deliver Python‑first engineering solutions for industry applications, collaborating with the Vertical Solutions Product Manager and customers to define the roadmap.

You will work closely with CAD/CAE specialists to implement, maintain, and evolve these workflows, identify reusable components for the platform, and help accelerate adoption across applications in a hybrid Cambridge-based setting.