Besque
Software Engineer
Skills
6 days ago
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Important information
Contract type:
Permanent
Location:
Bingley, UK
Work mode:
Onsite
Published on:
13 October 2026
What they need
This is a hands-on role for engineers with strong full-stack development experience and practical expertise in large language models. You will take AI solutions from concept or prototype through to production, including deployment within cloud and self-hosted environments.
You will be expected to work independently, make sound technical decisions, and take end-to-end ownership of delivery.
Responsibilities
Design, build, and maintain production-grade AI applications and services
Convert AI prototypes into secure, reliable, and scalable production systems
Develop full-stack solutions across front end, back-end, APIs, databases, and infrastructure
Deploy and operate applications on AWS, Google Cloud, and self-hosted infrastructure
Build LLM-powered workflows, agents, retrieval-augmented generation systems, integrations, and automation
Integrate AI applications with internal systems, databases, APIs, and third-party platforms
Evaluate models, architectures, and tools based on accuracy, reliability, latency, security, and cost
Implement appropriate testing, evaluation, monitoring, logging, and observability
Diagnose technical and production issues, identify root causes, and own resolution
Make pragmatic engineering decisions that balance delivery speed, quality, maintainability, and operational risk
Own solutions throughout their life cycle, from architecture and development to deployment and continuous improvement
Required Experience
Software Engineering
Strong commercial experience with JavaScript, Type Script, and Python
Experience building back-end services and REST APIs
Strong knowledge of SQL, relational databases, and data modelling
Experience developing and maintaining full-stack applications
Proficiency with Git, automated testing, code review, and modern development practices
Cloud and Infrastructure
Production experience with AWS and/or Google Cloud Platform
Experience with Docker and containerised application deployment
Practical knowledge of CI/CD pipelines
Experience deploying and operating self-hosted applications
Strong understanding of production monitoring, logging, security, and troubleshooting
AI and LLM Engineering
Proven experience building and deploying LLM-powered applications in production
Experience working with commercial and open-source language models
Strong understanding of prompt design, context management, structured outputs, and tool calling
Experience with RAG, embedding, vector databases, and retrieval systems
Experience building agentic or multi-step AI workflows
Understanding of LLM evaluation, observability, reliability, latency, and cost optimisation
Effective use of AI-assisted development tools to improve engineering productivity
Experience with technologies such as MCP, LangGraph, LangChain, LlamaIndex, Kubernetes, Terraform, or equivalent tools is advantageous. Strong engineering judgement and the ability to select the right technology are more important than experience with any specific framework.
What We Are Looking For
Ability to turn ambiguous business requirements into clear, practical technical solutions
Strong ownership and accountability from problem identification through to production delivery
Ability to work effectively with minimal supervision
A solution-oriented approach to technical and operational challenges
Strong root-cause analysis and problem-solving skills
Clear communication of technical options, trade-offs, risks, and recommendations
Ability to work across the technology stack when required
Capacity to learn unfamiliar technologies and codebases quickly
Focus on measurable outcomes rather than task completion alone
Ability to move quickly while maintaining appropriate engineering standards
What Success Looks Like
You can take ownership of a business problem without requiring a detailed implementation plan, determine the most appropriate technical approach, communicate your recommendation clearly, and deliver a reliable production solution.
You are comfortable building quickly, working across the stack, resolving complex technical issues, and taking responsibility for the ongoing performance of the systems you deliver.
To apply for this role please submit your CV to [email protected].
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