Lead Python Software Engineer

Wideopen
9 months ago
Applications closed

Related Jobs

View all jobs

Lead Software Engineer - MLOps

Lead Software Engineer - MLOps

Lead Software Engineer - Agentic AI/Machine Learning

Lead Software Engineer - MLOps Platform

Lead Software Engineer - Agentic AI/Machine Learning

Lead MLOps Engineer — Scalable AI for Banking

Job Title: Lead Python Software Engineer
Location: Newcastle (Hybrid WFH Available)
Salary: Up to £75,000 + benefits

KO2 Embedded Recruitment Solutions is proud to partner with a leading innovator in the smart industrial automation sector. Due to sustained growth and exciting new projects, our client is expanding their software development team and is now seeking a Lead Python Software Engineer to play a critical role in designing and delivering scalable, real-time software solutions.

The Role: As a Lead Python Software Engineer, you will take ownership of core backend development efforts, leading a small, agile team. You will be instrumental in architecting and building software systems that interface with real-time data sources and power intelligent automation platforms. This is a hands-on leadership position where you'll balance technical delivery with mentorship and team coordination.

Key Responsibilities:

Lead the design, development, and deployment of robust, scalable backend systems using Python and microservices architecture
Oversee code quality, testing, and DevOps practices to ensure continuous delivery
Collaborate closely with multidisciplinary teams, including hardware engineers and data scientists
Mentor and support junior developers and contribute to a high-performance engineering culture
Implement software solutions for real-time data processing in an industrial environment
Drive adoption of best practices in CI/CD, infrastructure automation, and system monitoringKey Skills and Experience:

Proven experience developing production-grade applications in Python
Working knowledge of C# for system integration and legacy support
Strong understanding of microservices architecture and containerization
Proficient in Linux environments for development and deployment
Hands-on experience with DevOps tools, ideally in an Azure cloud environment
Excellent problem-solving and leadership skillsDesirable:

Background in industrial automation, IoT, or embedded systems
Familiarity with protocols used in industrial environments
Experience with modern data pipelines or event-driven architecturesWhat's on Offer:

Competitive salary and benefits package
Flexible working hours and hybrid options
Career growth in a cutting-edge technology environment
A chance to influence and shape the direction of next-gen automation platformsTo apply, please contact KO2 Embedded Recruitment Solutions or send your CV directly to us today

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

How Many AI Tools Do You Need to Know to Get an AI Job?

If you are job hunting in AI right now it can feel like you are drowning in tools. Every week there is a new framework, a new “must-learn” platform or a new productivity app that everyone on LinkedIn seems to be using. The result is predictable: job seekers panic-learn a long list of tools without actually getting better at delivering outcomes. Here is the truth most hiring managers will quietly agree with. They do not hire you because you know 27 tools. They hire you because you can solve a problem, communicate trade-offs, ship something reliable and improve it with feedback. Tools matter, but only in service of outcomes. So how many AI tools do you actually need to know? For most AI job seekers: fewer than you think. You need a tight core toolkit plus a role-specific layer. Everything else is optional. This guide breaks it down clearly, gives you a simple framework to choose what to learn and shows you how to present your toolset on your CV, portfolio and interviews.

What Hiring Managers Look for First in AI Job Applications (UK Guide)

Hiring managers do not start by reading your CV line-by-line. They scan for signals. In AI roles especially, they are looking for proof that you can ship, learn fast, communicate clearly & work safely with data and systems. The best applications make those signals obvious in the first 10–20 seconds. This guide breaks down what hiring managers typically look for first in AI applications in the UK market, how to present it on your CV, LinkedIn & portfolio, and the most common reasons strong candidates get overlooked. Use it as a checklist to tighten your application before you click apply.

The Skills Gap in AI Jobs: What Universities Aren’t Teaching

Artificial intelligence is no longer a future concept. It is already reshaping how businesses operate, how decisions are made, and how entire industries compete. From finance and healthcare to retail, manufacturing, defence, and climate science, AI is embedded in critical systems across the UK economy. Yet despite unprecedented demand for AI talent, employers continue to report severe recruitment challenges. Vacancies remain open for months. Salaries rise year on year. Candidates with impressive academic credentials often fail technical interviews. At the heart of this disconnect lies a growing and uncomfortable truth: Universities are not fully preparing graduates for real-world AI jobs. This article explores the AI skills gap in depth—what is missing from many university programmes, why the gap persists, what employers actually want, and how jobseekers can bridge the divide to build a successful career in artificial intelligence.