Junior AI Engineer

Reply Ltd

Manchester, UK

6 days ago

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Role details

Contract type

Permanent contract

Employment type

Full-time (> 32 hours)

Experience level

Starter

Experience required

0 years minimum

Working hours

Regular working hours

Job source

www.collegerecruiter.com

Tech stack

Application Programming Interfaces (APIs) Artificial Intelligence Business Logic Microsoft Azure Cloud Computing Databases Continuous Integration Data Infrastructure Machine Learning Azure Machine Learning Software Engineering Systems Integration

+4 more

Backend Git Low-code Docker

Job description

Build bespoke AI agents, integrations, and the data foundations that make them reliable, using whichever language or tool best fits the problem.
Develop across the full stack - from backend application logic and APIs to front-end interfaces and cloud infrastructure - based on what each use case actually needs.
Work hands-on with the Microsoft AI stack (Azure OpenAI, Azure AI Foundry, Azure Machine Learning, Cognitive Services) in real production builds, not just sandbox demos.
Help shape delivery approaches, understanding when a use case genuinely needs pro-code and when a lighter-touch or low-code option is the honest answer.
Take ownership for your slice of each build, ensuring the clarity, reliability, and quality of what you ship.
Prototype and experiment with new AI tools, frameworks, and development techniques - including AI-assisted engineering - and share what you learn with the wider team.
Collaborate with colleagues and, over time, clients to explain what you’ve built, how it works, and the trade-offs behind key technical decisions.
Continuously push your own learning, picking up new parts of the stack as needed rather than staying fixed to one technology or layer.

Requirements

Early-career developer (graduate or 0-2 years’ experience) with a solid grounding in software engineering and clean, working code.
Demonstrated exposure to AI/ML concepts or tools (coursework, projects, or self-taught) and a genuine interest in real-world generative AI applications.
Self-starter who experiments, learns fast, and can independently pick up new tools, frameworks, and concepts when the problem demands it.
Clear and concise communicator, able to explain what they’ve built and why to both technical and non-technical audiences.
Generalist mindset, preferring to learn whatever piece of the stack the use case needs rather than staying in a narrow lane.
Comfortable using modern engineering practices and tooling (e.g. Git, CI/CD, Docker, databases) or motivated to ramp up quickly.
Curious, hands-on, and motivated by shipping real products to users rather than working only on theoretical or sandbox exercises.