Software Engineer

St James's
9 months ago
Applications closed

Related Jobs

View all jobs

Software Engineer - Large Language Models

Software Engineer - Large Language Models

Software Engineer - Large Language Models

Software Engineer - Large Language Models

Software Engineer - Large Language Models

Software Engineer - Large Language Models

Our energy client is seeking a software engineer to join their team in Mayfair, London.
We are looking for a Senior Backend Software Engineer with strong data engineering skills to join a small, agile team developing software solutions for our energy supply and trading functions.
Hybrid working is in play, with 3 days in the office and 2 days at home.
Software Engineer- About the role:
My client’s energy business is growing rapidly with a strong focus on using advanced data systems and analytics to deliver exceptional service. We are looking for someone to take ownership of the backend architecture that underpins our analytics applications, user tools, and automated trading workflows.
You will collaborate closely with analysts, data scientists, and business stakeholders to translate requirements into robust, scalable backend solutions. You’ll be responsible for designing and developing services, APIs, data pipelines, and internal applications that integrate analytics and enable better decision-making and operational efficiency.
This is a hands-on role for someone who thrives in a fast-paced, build-first culture without multiple tiers of management. You should be excited to take full ownership of backend development, lead on best practices, and coach others in a collaborative, delivery-focused team.
Experience in retail or wholesale electricity and gas markets is helpful, but a willingness to become an expert in this field is essential. Our success is based on understanding the subject matter from first principles.
Software Engineer - Key Responsibilities:

  • Architect, design, develop and maintain backend systems for analytics-driven applications, user tools, and automation workflows.
  • Build and manage APIs and internal services using Python (FastAPI, Flask) and cloud-native tooling.
  • Develop and manage data pipelines, backend components, and supporting infrastructure.
  • Manage server resources and backend processing environments to ensure reliability and scalability.
  • Monitor and maintain application performance, availability, and data quality across production systems.
  • Implement and maintain CI/CD pipelines, testing frameworks, and DevOps practices to enable robust delivery.
  • Write, test, and document code in line with quality standards and engineering best practices.
  • Collaborate with operations, analytics and commercial teams to gather requirements and translate them into scalable technical solutions.
  • Support analysts and data scientists in deploying and operationalising analytics tools and models.
  • Lead or support the data engineering team, help structure development workflows, and mentor junior team members.
    Software Engineer - Skills Required:
  • Python (FastAPI, Flask) (or another asynchronous language/framework)
  • REST API development
  • RabbitMQ / Message queue
  • PostgreSQL
  • Databricks
  • Containerisation: Docker, Kubernetes
  • CI/CD: Azure DevOps, GitHub Actions
  • Relational databases and data lake architecture
  • Model and data pipeline integration (e.g. MLflow)
  • Microsoft Azure (Functions, Storage, Compute)
  • Monitoring tools (Grafana, Prometheus, etc.)
  • Mentoring and knowledge sharing within the team
    Senior Engineer - Desirable Skills:
  • Experience in energy supply or trading
  • Familiarity with dbt or modular analytics tooling
  • Exposure to forecasting or optimisation workflows
  • Knowledge of React or frontend tools for internal apps
    What they offer:
  • A high-autonomy role in a flat, delivery-focused team
  • Ownership of backend systems for real-time analytics and automation
  • A fast-moving, hands-on culture with meaningful technical challenges
  • The opportunity to apply software and data engineering to real-world energy problems

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 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.

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.