Senior Backend Software Engineer / Team Lead (N.Ireland)

Camlin Group
Lisburn
11 months ago
Applications closed

Related Jobs

View all jobs

Senior Machine Learning Engineer

Senior Data Engineer - GFT Halifax

Remote Senior Data Engineer (m/f/d)

Senior Data Analyst

Senior Machine Learning Engineer

Senior Data Engineer

COMPANY DESCRIPTION

At Camlin we pride ourselves on designing and building complete solutions in-house. We create everything from hardware PCB designs to device firmware, Linux drivers, IoT application software, server software, server web UIs, mobile apps, and machine learning and data science solutions. We believe that by controlling every aspect of the development process, we can deliver truly unique and exceptional products to our customers.

Our advanced technology stack includes the use of REST APIs, MQTT and RabbitMQ queues, Docker, and open-source tools. We are constantly looking for new and innovative ways to improve our products and processes, and we believe that by using the latest technologies, we can continue to lead the industry.

As a member of our team, you will have the opportunity to work with a variety of technologies and collaborate with experts in the field of digital signal processing, data acquisition, complex connected devices, machine learning, and data science. You will have the opportunity to work on exciting projects and see your ideas come to life, and you will be part of a team that is committed to creating solutions that make a difference.

If you are a passionate programmer who is looking to work on challenging projects and be part of a team that is dedicated to innovation, then we want to hear from you. Join us and be part of a company that is changing the world with our cutting-edge IoT devices and an advanced technology stack.



WHAT TO EXPECT DAY TO DAY

We are looking for talented engineers to join development team as Senior Backend Engineer / Team Lead and work on existing project that involves developing backend solutions that will enable visualization of data collected from IOT devices that monitors electrical grid, visualization of current assets and their displacement, etc.


As a Senior Backend Engineer, you can expect to work in a dynamic and innovative environment, collaborating with multi-disciplinary teams to develop cutting – edge solutions. Day to day, you"ll be working on developing and maintaining backend microservices and their APIs, deployment pipelines, infrastructure challenges and much more. You will be in close collaboration with Frontend Engineers, Data Engineers, DevOps and Product Owners and Scrum Master.

The team is working on a system that monitors and analyses the state of the electrical grid and sends out alerts when faults or power disruptions occur, helping keep the lights on for end consumers. It also provides comprehensive analysis for the assets based on the various data that are coming from the entire energy system. You"ll have the opportunity to work with the latest technologies and tools, including Python Fast API, MQTT, Docker, Kubernetes and much more. You"ll be encouraged to stay up to date with the latest trends and advancements in the industry, and to share your knowledge and ideas with the team.


In this role, you"ll be part of a team that is passionate about using technology to solve complex problems and make a real impact in the world. If you"re excited about the idea of working on a project that has the potential to change the way we think about energy, then we"d love to hear from you!


Part of the role will be a team lead duty that requires leading team of junior and medior developers (up to 5 team members), mentoring them, provide regular feedback, removing obstacles and ensure project delivery on time.


TECH STACK

  • Python (Fast API)
  • Docker
  • Kubernetes
  • Ubuntu Linux
  • RabbitMQ
  • Ubuntu Linux
  • AWS
  • MySQL, PostgreSQL, AWS Aurora,
  • GitLab CI

RESPONSIBILITIES

  • Design and development of backend microservices
  • Maintenance and migration of applications to modern Python frameworks
  • Development of automated unit and component tests
  • Contribution to Camlin's software development strategies
  • Participation in Agile Scrum and design meetings
  • Governance of application CI/CD pipelines
  • Design and development of web application security
  • Leading a team up to 5 team members
  • Technical mentorship of frontend engineers

WHAT YOU"LL NEED

  • Experience as a Backend Software Engineer
  • Experience designing and implementing REST APIs (Fast API)
  • Experience working with SQL databases
  • Bachelor"s degree in computer software engineering or equivalent
  • Practical knowledge of Linux (CLI, bash)
  • Experience mentoring and leading engineering team
  • Practical knowledge of modern web application deployment infrastructures
  • Fluency in English, written and verbal
  • Strong knowledge of SDLC

NICE TO HAVE:

  • Experience building SaaS applications
  • Knowledge of secure software development principles
  • Knowledge of Docker & Kubernetes
  • Experience working with message queue systems, e.g. RabbitMQ or MQTT
  • Knowledge of version control systems, e.g. Git
  • Experience with AWS
  • Experience with external monitoring tools


BENEFITS

  • Competitive salary
  • Company Pension & Life Assurance Schemes
  • On-site parking
  • Smart / Remote Working
  • Subsidised Gym Membership
  • Wellness programmes


EQUAL EMPLOYMENT OPPORTUNITY STATEMENT

Individuals seeking employment at Camlin are considered without regards to race, colour, religion, national origin, age, sex, marital status, ancestry, physical or mental disability, gender identity, or sexual orientation.



1ONwmXSAzXlD1i4gqHONmj

PI261354364

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.

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

Whether you’re applying for machine learning engineer, applied scientist, research scientist, ML Ops or data scientist roles, hiring managers scan applications quickly — often making decisions before they’ve read beyond the top third of your CV. In the competitive UK market, it’s not enough to list skills. You must send clear signals of relevance, delivery, impact, reasoning and readiness for production — and do it within the first few lines of your CV or portfolio. This guide walks you through exactly what hiring managers look for first in machine learning applications, how they evaluate CVs and portfolios, and what you can do to improve your chances of getting shortlisted at every stage — from your CV and LinkedIn profile to your cover letter and project portfolio.

MLOps Jobs in the UK: The Complete Career Guide for Machine Learning Professionals

Machine learning has moved from experimentation to production at scale. As a result, MLOps jobs have become some of the most in-demand and best-paid roles in the UK tech market. For job seekers with experience in machine learning, data science, software engineering or cloud infrastructure, MLOps represents a powerful career pivot or progression. This guide is designed to help you understand what MLOps roles involve, which skills employers are hiring for, how to transition into MLOps, salary expectations in the UK, and how to land your next role using specialist platforms like MachineLearningJobs.co.uk.

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

Machine learning has moved from academic research into the core of modern business. From recommendation engines and fraud detection to medical imaging, autonomous systems and language models, machine learning now underpins many of the UK’s most critical technologies. Universities have responded quickly. Machine learning modules are now standard in computer science degrees, specialist MSc programmes have proliferated, and online courses promise to fast-track careers in the field. And yet, despite this growth in education, UK employers consistently report the same problem: Many candidates with machine learning qualifications are not job-ready. Roles remain open for months. Interview processes filter out large numbers of applicants. Graduates with strong theoretical knowledge struggle when faced with practical tasks. The issue is not intelligence or effort. It is a persistent skills gap between university-level machine learning education and real-world machine learning jobs. This article explores that gap in depth: what universities teach well, what they routinely miss, why the gap exists, what employers actually want, and how jobseekers can bridge the divide to build successful careers in machine learning.