Senior Software Engineer - Backend & Machine Learning

Raft
gb
10 months ago
Applications closed

Related Jobs

View all jobs

Senior MLOPs Engineer

Senior Simulation Engineer (Data Science)

Lead Software Engineer (Machine Learning)

Senior Machine Learning Engineer, Gen AI

Senior Machine Learning Engineer

Machine Learning Engineer Python AWS

Raft, an intelligent logistics platform, is revolutionizing the freight and customs industry through automation and advanced technologies. As a fast-scaling, UK-based tech company with global reach, we're pioneering solutions that empower freight forwarders and customs brokers to operate at new levels of efficiency and precision. Fueled by our Series B funding from renowned investors, we're poised for major growth and innovation.

As a Senior Backend Engineer with a focus on LLM/AI at Raft, you'll be instrumental in shaping the architecture and capabilities of our platform to support cutting-edge logistics features powered by AI. This is not a traditional engineering role—it's a high-impact opportunity where you'll design robust cloud infrastructure, develop scalable APIs, and enhance our data pipeline ecosystem to support AI/ML workloads. You will be responsible for creating highly resilient systems, enabling features such as natural language processing, predictive analytics, and real-time decision-making. In addition to building advanced software, you'll play a strategic role in driving technical decision-making and mentoring our growing engineering team. This role is for someone who thrives in a fast-paced, ambitious environment and is ready to make an outsized impact on a product used across the globe.

What You'll Do:

  • Architect, build, and maintain scalable, cloud-based infrastructure to support LLM and AI workloads.
  • Design, implement, and maintain sophisticated databases, APIs, and data pipelines optimized for AI/ML applications.
  • Integrate LLM and AI models into the Raft platform to power new and innovative features.
  • Drive the evolution of platform features that require complex engineering solutions powered by AI/ML.
  • Collaborate across functions to ensure our platform is secure, reliable, and optimized for performance.

Requirements

  • Brings 7+ years of hands-on experience in backend development with a strong focus on Python, supplemented by experience in other programming languages.
  • Has deep expertise in designing and maintaining scalable databases (preferably PostgreSQL) and understands the latest trends in database technology, particularly relevant to LLM and AI applications.
  • Is proficient with FastAPI/Starlette and can demonstrate experience in building scalable APIs with Python for AI/ML applications.
  • Has a solid track record in multi-cloud environments and understands how to architect and implement software libraries that thrive in distributed, multi-cloud settings.
  • Can design and implement a sophisticated logging, monitoring, and alerting infrastructure to ensure high availability and quick troubleshooting of AI/ML systems.
  • Understands and implements best practices in security and data privacy, with a proven ability to secure complex data flows, particularly for LLM/AI applications.
  • Has extensive experience with containerised tools like Docker, Docker Compose, Kubernetes, Helm, and understands the intricacies of deploying these in production, specifically for LLM/AI workloads.

Apply Because You Want to...

  • Join a company on the leading edge of logistics technology, competing with industry giants while leveraging cutting-edge AI/ML and backend engineering.
  • Work in a product-driven environment where your contributions shape real-world solutions for a global customer base.
  • Collaborate with stakeholders across industries and continents, gaining unparalleled exposure to the logistics and automation sectors.
  • Thrive in a high-energy, growth-focused environment that pushes you to expand your technical and strategic skill sets.
  • Be part of a diverse, inclusive, and multi-cultural team where innovation and continuous improvement are celebrated.

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.