Technical Lead - Software Engineer (Full Stack) Bristol

Bristol
2 months ago
Applications closed

Related Jobs

View all jobs

Technical Intern

Technical Intern

Technical Intern

Technical Intern

Technical Intern

Technical Intern

Job Title: Technical Lead (Software Engineer) (Full stack)- Python, PySpark, HPC
Salary: £100,000 - £130,000 | Location: Bristol, UK (Hybrid)

About the Company

My client is a pioneering InsurTech specialising in cyber reinsurance, delivering advanced analytic's and underwriting solutions that transform cyber risk management. Their skilled, collaborative team thrives on data science and engineering innovation.

The Role: Technical Lead

We're seeking a hands-on Technical Lead to drive platform development, build and lead a high-performing engineering team, and integrate advanced risk modelling into their cyber reinsurance platform. This role requires 10+ years' experience in software engineering, including 5+ years in leadership, preferably in insurance or financial services.

Key Responsibilities

Platform Development: Architect and develop acyber reinsurance platform, incorporating:
Reinsurance submission ingestion, policy administration, cyber risk modelling, portfolio optimisation, and advanced reporting.
Team Leadership: Build and manage a high-performance engineering team across HPC, data engineering, and web development.
Collaboration: Work closely with data science and modelling teams to integrate analytical models.
Scaling Strategy: Expand the platform across new business lines.
Hands-On Contribution: Remain actively involved in the codebase, solving technical challenges and mentoring the team.

Qualifications & Skills

10+ years in software engineering, you must be experienced across the Full stack both Front and Back End with 5+ years in leadership (preferably in insurance).
Strong Python and PySpark skills, plus HPC, large-scale data engineering, and full-stack development.
Experience with machine learning, cloud platforms (AWS, GCP, Azure), DevOps tools (Docker, Terraform, Kubernetes), and data lakehouses (Databricks).
Proven success in building and scaling engineering teams and aligning initiatives with business goals.

Why Join?

Lead a cutting-edge team in cyber reinsurance.
Shape the future of risk management with advanced analytics.
Work in a highly collaborative, innovative environment.

How to Apply

Send your CV to to explore this opportunity

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.

Jobs

Portfolio Projects That Get You Hired for AI Jobs (With Real GitHub Examples)

In the fast-evolving world of artificial intelligence (AI), an impressive portfolio of projects can act as your passport to landing a sought-after role. Even if you’ve aced interviews in the past, employers in AI and machine learning (ML) are increasingly asking candidates to demonstrate hands-on experience through the projects they’ve built and shared online. This is because practical ability often speaks volumes about your suitability for a role—far more than any exam or certification alone could. In this article, we’ll explore how to build an outstanding AI portfolio that catches the eye of recruiters and hiring managers, including: Why an AI portfolio is crucial for job seekers. How to choose AI projects that align with your target roles. Specific project ideas and real GitHub examples to help you stand out. Best practices for showcasing your work, from writing clear READMEs to using Jupyter notebooks effectively. Tips on structuring your GitHub so that employers can instantly see your value. Moreover, we’ll discuss how you can use your portfolio to connect with top employers in AI, with a handy link to our CV-upload page on Artificial Intelligence Jobs for when you’re ready to apply. By the end, you’ll have a clear roadmap to building a portfolio that will help secure interviews—and the AI job—of your dreams.

Jobs Careers

AI Job Interview Warm‑Up: 30 Real Coding & System‑Design Questions

In today's competitive AI job market, nailing a technical interview can be the difference between landing your dream role and getting lost in the crowd. Whether you're looking to break into machine learning, deep learning, NLP (Natural Language Processing), or data science, your problem-solving skills and system design expertise are certain to be put to the test. AI‑related job interviews typically involve a range of coding challenges, algorithmic puzzles, and system design questions. You’ll often be asked to delve into the principles of machine learning pipelines, discuss how to optimise large-scale systems, and demonstrate your coding proficiency in languages like Python, C++, or Java. Adequate preparation not only boosts your confidence but also reduces the likelihood of fumbling through unfamiliar territory. If you’re actively seeking positions at major tech companies or innovative AI start-ups, then check out www.artificialintelligencejobs.co.uk for some of the latest vacancies in the UK. Meanwhile, this blog post will guide you through 30 real coding & system-design questions you’re likely to encounter during your AI job interview. This list is designed to help you practise, anticipate typical question patterns, and stay ahead of the competition. By reading through each question and thinking about the possible approaches, you’ll sharpen your problem-solving skills, time management, and critical thinking. Each question covers fundamental concepts that employers regularly test, ensuring you’re well-equipped for success. Let’s dive right in.

Jobs

Negotiating Your AI Job Offer: Equity, Bonuses & Perks Explained

Artificial intelligence (AI) has proven itself to be one of the most transformative forces in today’s business world. From smart chatbots in customer service to predictive analytics in finance, AI technologies are reshaping how organisations operate and innovate. As the demand for AI professionals grows, so does the complexity of compensation packages. If you’re a mid‑senior AI professional, you’ve likely seen job offers that include far more than just a base salary—think equity, bonuses, and a range of perks designed to entice you into joining or staying with a company. For many, the focus remains squarely on salary. While that’s understandable—after all, your monthly take‑home pay is what covers day-to-day expenses—limiting your negotiations to salary alone can leave considerable value on the table. From stock options in ambitious startups to sign‑on bonuses that ‘buy you out’ of your current contract, modern AI job offers often include elements that can significantly boost your long-term wealth and job satisfaction. This article aims to shed light on the full scope of AI compensation—specifically focusing on how equity, bonuses, and perks can enhance (or sometimes detract from) the overall value of your package. We’ll delve into how these elements work in practice, what to watch out for, and how to navigate the negotiation process effectively. Our goal is to provide mid‑senior AI professionals with the insights and tools to land a holistic compensation deal that accurately reflects their technical expertise, leadership potential, and strategic importance in this fast-moving field. Whether you’re eyeing a leadership role in machine learning at an established tech giant, or you’re considering a pioneering position at a disruptive AI startup, the knowledge in this guide will help you weigh the merits of base salary alongside the potential riches—and risks—of equity, bonuses, and other benefits. By the end, you’ll have a clearer sense of how to align your compensation with both your immediate lifestyle needs and long-term career aspirations.

🍪 We use cookies to enhance your browsing experience on our website. By continuing to use this site, you consent to the use of cookies as described in our Cookie Policy. You can review our Cookie Policy for more information.