Python Developer - Security - Cambridge/London
Summary
A mid-level Python engineer builds backend services and turns research/prototype outputs into production-ready features in a security-focused, research-driven environment. Day to day involves Python development, Docker/CI-CD workflows, cloud deployment, debugging, and close collaboration with ML/AI researchers, SREs, and product managers in a hybrid Cambridge/London setup.
Python Developer - Security - Cambridge/London
Salary: 55k - 75k
Hybrid: 1 - 2 days per week
Start: ASAP
My new client is looking for a problem-solving focused mid-level Python engineer (specialist) who wants to build product features in a research-driven environment. You'll be expected to contribute to product development, deliver clean, testable Python code, collaborate with small cross-functional teams, and communicate your thinking clearly in high-cadence development cycles.
Key Responsibilities
- Design, implement, test, and maintain backend services and prototypes in Python.
- Work from prototype/research outputs to production-ready components alongside ML/AI researchers and SREs.
- Participate in live coding/problem-solving rounds during development and code reviews.
- Collaborate closely with product managers and researchers to translate ideas into working demos and production features.
- Help troubleshoot, debug, and optimise systems (performance, reliability, observability).
- Contribute to CI/CD, containerisation (Docker) workflows, and cloud deployment patterns as required.
- Communicate trade-offs and design decisions clearly; adapt to changing requirements.
Required Skills & Experience
- Strong Python proficiency (day-to-day production experience).
- Demonstrable problem-solving aptitude - ability to break down ambiguous problems and explain reasoning clearly.
- Experience working in small teams or fast-moving product environments where engineers wear multiple hats.
- Practical familiarity with containers (Docker) and general cloud concepts.
- Good communication skills - able to think out loud during live problem-solving.
- Typically 3+ years' relevant experience (flexible; equivalent experience or strong demonstrable ability considered).
Desirable (but not required)
- Experience with Kubernetes or container orchestration.
- Exposure to ML/AI projects, data pipelines, or research-driven engineering.
- Experience with observability tooling, CI/CD, and testing best practices.
- Degree in Computer Science, Engineering, or related technical field (or demonstrable equivalent).
Rates depend on experience and client requirements