Senior AI Developer - Detillens

Detillens
Glasgow, United Kingdom
yesterday

Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Working hours
Regular working hours
Languages
English
Experience level
Senior

Job location

Glasgow, United Kingdom

Tech stack

Java
Multitier Architecture
Artificial Intelligence
Software Applications
Computing Platforms
Architectural Patterns
Cloud Computing
Continuous Integration
Command-Query Responsibility Segregation (Software Development)
DevOps
Distributed Systems
Interoperability
Python
Machine Learning
Software Architecture
Software Construction
Software Engineering
Systems Architecture
Systems Integration
Modern Ui
Large Language Models
Generative AI
Backend
Event Driven Architecture
Kubernetes
Api Design
Domain Driven Design
Programming Languages
Microservices

Job description

We are seeking an experienced and forward-thinking Senior Software Engineer to play a key role in driving a large-scale AI and intelligent automation agenda within a complex technology environment.

This is not a traditional software engineering role. We are looking for someone who combines strong full-stack development expertise with a genuine passion for AI, systems architecture, and business transformation. You will help identify, design, build, deploy and embed AI-powered solutions and agent-based workflows that deliver measurable business impact.

This opportunity is ideal for someone who wants to work in an AI-first environment where artificial intelligence is already being actively leveraged across engineering teams and business processes. You'll be joining a highly visible team with significant investment, ambitious objectives and the opportunity to influence technical direction.

What You'll Be Doing:

  1. Design, build and deploy AI-powered applications, services and intelligent agents that automate and enhance business workflows.
  2. Partner with stakeholders to identify opportunities where AI can create efficiency, scalability and operational improvements.
  3. Drive end-to-end solution delivery across the full technology stack, from user-facing applications through to backend services and integrations.
  4. Contribute to technology strategy, systems design and architectural decision-making.
  5. Review and govern AI-generated code, ensuring quality, maintainability and long-term sustainability.
  6. Leverage modern AI-assisted engineering tools to accelerate delivery while maintaining robust engineering standards.
  7. Champion scalable, secure and interoperable technology solutions.
  8. Help shape the roadmap for AI adoption across the organisation and contribute to long-term innovation initiatives.
  9. Work within a fast-moving environment where experimentation, continuous learning and rapid execution are encouraged.

Requirements

  1. 8-12+ years software engineering experience within complex enterprise technology environments.
  2. Strong full-stack development capability with the ability to operate across multiple technologies and platforms.
  3. Experience designing and delivering scalable distributed systems.
  4. Proven understanding of software architecture and modern design principles.
  5. Practical experience building, deploying or integrating AI, machine learning, generative AI or agent-based solutions.
  6. Strong systems-thinking mindset with the ability to understand and optimise end-to-end business processes.
  7. Experience leveraging AI-assisted development tools and modern engineering practices.
  8. Ability to balance delivery speed with engineering quality and maintainability.
  9. Strong communication skills with the confidence to engage with technical and non-technical stakeholders.
  10. Python, Java or other modern programming languages.
  11. Microservices and distributed architectures.
  12. Architecture patterns including Domain-Driven Design (DDD), CQRS, Event-Driven Architecture and Clean Architecture.
  13. Cloud-native development and scalable platform design.
  14. API design, systems integration and interoperability.
  15. Workflow automation and orchestration frameworks.
  16. DevOps, CI/CD and software engineering best practices.
  17. AI frameworks, LLMs, agentic workflows and intelligent automation platforms.

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