Software Engineer Lead

Newark on Trent
10 months ago
Applications closed

Related Jobs

View all jobs

AI Lead, AI Engineer Lead, Generative AI Engineer, Machine Learning Engineer, AI Platform Engineer, NLP Engineer, Applied AI Engineer, AI Integration Specialist, AI Software Engineer, AI Systems Architect, AI Engineer, AI Development Lead,

Lead Software Engineer - Agentic AI/Machine Learning

Lead Software Engineer (Machine Learning)

Senior Staff Engineer (Machine Learning) - 45391

Senior Staff Engineer (Machine Learning) - 45391

Senior Staff Engineer (Machine Learning) - 45391

Software Engineer Lead
Newark, Full time, Permanent
Salary up to £50,000 per annum.
Our award-winning client, based in Newark, Nottinghamshire is seeking a motivated leader who will plan succession and development for their team, alongside overseeing development projects and maintaining key systems. The Software Engineer Lead is a full time, permanent position with the opportunity for hybrid working.
The Role
As Software Engineer Lead, your responsibilities will include:

  • Supporting and leading the Development team with collaboration and growth
  • Working on the development strategy
  • Overseeing software development projects
  • Implementing and enforcing best practices, coding standards and agile methodologies
  • Ensuring innovation, continuous improvement and technical excellence
  • Collaborating with stakeholders (this is inclusive of product management, operations and executive leadership)
  • Upgrading and maintaining key systems
    The Candidate
    An ideal candidate for the Software Engineer Lead position should hold the following skills:
  • At least 3 years proven experience in software development (including 1 year of leadership)
  • Hold a strong technical background (software architecture, coding, system design)
  • Be familiar with Agile development methodologies and DevOps practices
  • Have an understanding of cloud technologies, security principles and modern development tools
  • Knowledge of BI tools, data warehousing and system infrastructure
  • Proficient in API development using languages such as C# and .NET
  • Be familiar with databases including SQL
    You will have experience designing, developing and maintaining system integrations between applications, services and platforms.
    A Software Engineer Lead candidate will ideally possess the following:
  • Familiarity / experience with AI, machine learning or blockchain technologies
  • Prior experience on MDM’s
  • Knowledge of ServiceNow, Azure Dev Ops, Netsuite and Power BI
    Following an initial training period, the successful Software Engineer Lead will have the opportunity to work on a hybrid basis.
    The Company
  • Paid volunteer day
  • Onsite gym
  • Ongoing learning and development
  • Bonus paid day off for your birthday!
  • Annual wellbeing budget
  • Increasing annual leave
  • Company sick pay
    Thank you for your interest in this vacancy and good luck with your application.
    If you have not heard from a member of the Future Prospects team within 7 days from your application, please assume that your application has not been successful on this occasion. Unfortunately, due to the high volume of applications we receive, we are unable to provide individual feedback
    The services of Future Prospects are those of an Employment Agency

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.

AI Jobs for Career Switchers in Their 30s, 40s & 50s (UK Reality Check)

Changing career into artificial intelligence in your 30s, 40s or 50s is no longer unusual in the UK. It is happening quietly every day across fintech, healthcare, retail, manufacturing, government & professional services. But it is also surrounded by hype, fear & misinformation. This article is a realistic, UK-specific guide for career switchers who want the truth about AI jobs: what roles genuinely exist, what skills employers actually hire for, how long retraining really takes & whether age is a barrier (spoiler: not in the way people think). If you are considering a move into AI but want facts rather than Silicon Valley fantasy, this is for you.

How to Write an AI Job Ad That Attracts the Right People

Artificial intelligence is now embedded across almost every sector of the UK economy. From fintech and healthcare to retail, defence and climate tech, organisations are competing for AI talent at an unprecedented pace. Yet despite the volume of AI job adverts online, many employers struggle to attract the right candidates. Roles are flooded with unsuitable applications, while highly capable AI professionals scroll past adverts that feel vague, inflated or disconnected from reality. In most cases, the issue isn’t a shortage of AI talent — it’s the quality of the job advert. Writing an effective AI job ad requires more care than traditional tech hiring. AI professionals are analytical, sceptical of hype and highly selective about where they apply. A poorly written advert doesn’t just fail to convert — it actively damages your credibility. This guide explains how to write an AI job ad that attracts the right people, filters out mismatches and positions your organisation as a serious employer in the AI space.

Maths for AI Jobs: The Only Topics You Actually Need (& How to Learn Them)

If you are a software engineer, data scientist or analyst looking to move into AI or you are a UK undergraduate or postgraduate in computer science, maths, engineering or a related subject applying for AI roles, the maths can feel like the biggest barrier. Job descriptions say “strong maths” or “solid fundamentals” but rarely spell out what that means day to day. The good news is you do not need a full maths degree worth of theory to start applying. For most UK roles like Machine Learning Engineer, AI Engineer, Data Scientist, Applied Scientist, NLP Engineer or Computer Vision Engineer, the maths you actually use again & again is concentrated in a handful of topics: Linear algebra essentials Probability & statistics for uncertainty & evaluation Calculus essentials for gradients & backprop Optimisation basics for training & tuning A small amount of discrete maths for practical reasoning This guide turns vague requirements into a clear checklist, a 6-week learning plan & portfolio projects that prove you can translate maths into working code.