Principal Software Engineer

ProBox Recruitment Ltd
Lincoln
2 days ago
Create job alert

All applicants must be a UK national to be considered for this opportunity due to the nature of this role and to allow for government security vetting (UKSV).My client is a software house, developing and delivering innovative solutions through a dynamic team of experienced professionals and graduates. There is a strong culture with a collaborative working environment that promotes growth, creativity, and excellence. They are currently looking to recruit a dedicated and experienced Principal Full Stack Software Engineer/Developer with a minimum of 8 years of relevant experience to join their expanding team. This is a leadership role that encompasses all aspects of the software development lifecycle, from requirements capture to design, implementation, documentation, and testing. The successful candidate will thrive in an agile framework and will play a critical role in mentoring and leading a team of over 30 engineers.Key Responsibilities:Provide guidance, mentorship, and upskilling for team members, conducting code reviews and defining best practices.Allocate work and break down technical tasks effectively.Engage in system design and application/database development.Ensure software assurance and quality through component, integration, and system testing.Document design processes and maintain accurate project records.Qualifications/Experience:Essential:A relevant degree in Computing/Engineering/Mathematics (STEM) and at least 8 years of software development experience.Proven experience leading technical projects.In-depth knowledge of system architecture, microservices, APIs, and cloud technologies.Proficiency in one or more coding languages, including:

Web Development: HTML/CSS/JS/ReactASP.Net C#PHPC#PythonJavaScriptSQL

Desirable:Familiarity with UI/UX best practices and application deployment/maintenance.Experience with relational and document/NoSQL databases.Knowledge of Agile/DevOps methodologies and CI/CD pipelines.Exposure to machine learning principles and tools (e.g., PyTorch, TensorFlow).Understanding of cloud services (Azure, AWS, GCP) and technologies like Docker and Kubernetes.Experience with version control systems (Git) and testing frameworks (Puppeteer, Jest).Personal Attributes:Strong problem-solving skills and a proactive, can-do attitude.Excellent communication skills, both written and oral.Ability to adapt and lead through change in a fast-paced environment.A self-starter with the capability to work independently and collaboratively.Benefits:Private health care and sickness cover.Salary sacrifice options.Company socials.Breakout areas with drinks and snacks.A vibrant team culture that encourages professional development and personal growth.

Related Jobs

View all jobs

Principal Software Engineer

Principal Software Engineer

Principal Software Engineer

Senior/Principal Software Engineer

Senior/Principal Software Engineer

Senior/Principal Software Engineer

Get the latest insights and jobs direct. Sign up for our newsletter.

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

Industry Insights

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

Machine Learning Leadership for Managers: Strategies to Motivate, Mentor, and Set Realistic Goals in Data-Driven Teams

Machine learning (ML) has become an indispensable force in the modern business world, influencing everything from targeted marketing campaigns to advanced medical diagnostics. As industries integrate predictive algorithms and data-driven decision-making into their core operations, the need for effective leadership in machine learning environments has never been greater. Whether you’re overseeing a small team of data scientists or spearheading an enterprise-scale ML project, your leadership style must accommodate rapid innovation, complex problem-solving, and diverse stakeholder expectations. This guide provides actionable insights into how you can motivate, mentor, and establish achievable goals for your machine learning teams—ensuring they thrive in data-driven environments.

Top 10 Books to Advance Your Machine Learning Career in the UK

Machine learning (ML) remains one of the fastest-growing fields within technology, reshaping industries across the UK from finance and healthcare to e-commerce, telecommunications, and beyond. With increasing demand for ML specialists, job seekers who continually update their knowledge and skills hold a significant advantage. In this article, we've curated ten essential books every machine learning professional or aspiring ML engineer in the UK should read. Covering foundational theory, practical implementations, advanced techniques, and industry trends, these resources will equip you to excel in your machine learning career.

Navigating Machine Learning Career Fairs Like a Pro: Preparing Your Pitch, Questions to Ask, and Follow-Up Strategies to Stand Out

Machine learning (ML) has swiftly become one of the most in-demand skill areas across industries, with companies leveraging predictive models and data-driven insights to solve challenges in healthcare, finance, retail, manufacturing, and beyond. Whether you’re an early-career data scientist aiming to break into ML, a seasoned engineer branching into deep learning, or a product manager exploring AI-driven solutions, machine learning career fairs offer a powerful route to connect with prospective employers face-to-face. Attending these events can help you: Network with hiring managers and technical leads who make direct recruitment decisions. Gain insider insights on the latest ML trends and tools. Learn about emerging job roles and new industry verticals adopting machine learning. Showcase your interpersonal and communication skills, both of which are increasingly important in collaborative AI/ML environments. However, with many applicants vying for attention in a bustling hall, standing out isn’t always easy. In this detailed guide, we’ll walk you through how to prepare meticulously, pitch yourself confidently, ask relevant questions, and follow up effectively to land the machine learning opportunity that aligns with your ambitions.