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Software Engineer, Backend Developer, AI Engineer (Applied​/Software)

Job in Cambridge, Cambridgeshire, CB21, England, UK
Listing for: Frontier Agriculture SA
Full Time position
Listed on 2026-10-26
Job specializations:
  • Software Development
    Backend Developer, AI Engineer (Applied/Software), Python, Full Stack Developer
Salary/Wage Range or Industry Benchmark: 65000 - 90000 GBP Yearly GBP 65000.00 90000.00 YEAR
Job Description & How to Apply Below

YAGRO Ltd () are seeking a Mid Software Engineer with strong Python and Type Script skills and practical experience integrating AI into production applications. The role is responsible for building and maintaining enterprise Software as a Service (SaaS) and white label technology solutions for agri-food enterprises. Working alongside senior engineers, you will take ownership of development tasks, contribute across the stack and help deliver reliable, user-friendly software, applying AI where it adds value.

You will bring two to five years of professional software development experience and a relevant degree or a proven track record of delivering production-quality software.

Whilst this is a largely remote role, you will be required to attend the Cambridge office one day a week.

Key Responsibilities Technical Proficiency & Problem Solving:

Build and maintain production-quality software using Python and Type Script, applying sound engineering principles, design patterns and modular code structure. Develop applications using Vue 3 and Nuxt in SPA mode, or equivalent reactive frameworks, alongside asynchronous Python services using FastAPI or equivalent technologies. Work confidently with relational databases, preferably PostgreSQL, and SQL. Break down technical problems, diagnose and resolve bugs, and contribute scalable, maintainable solutions with guidance from senior engineers where needed.

Understand multi-stage asynchronous processing pipelines and take ownership of individual stages, including uploading, validating, processing and storing data. Integrate LLM or ML model APIs into production features, writing and reviewing prompts with appropriate safeguards against prompt injection and invalid outputs.

Project Contribution &

Collaboration:

Take ownership of assigned work from development through deployment, showing initiative and communicating progress, dependencies and challenges early. Contribute to planning and delivery using Agile/Scrum or equivalent methods and collaboration tools such as Git Hub, Git Lab and Jira. Work effectively with engineering, Product, QA and design colleagues, participating in code reviews and providing constructive feedback. Share knowledge, support colleagues and, where appropriate, help onboard new team members.

Work alongside senior engineers, including colleagues experienced in AI and retrieval-augmented generation (RAG), to build the team’s confidence in applying AI to practical problems. Contribute to frontend and backend work according to your experience, developing a broader understanding of APIs, distributed systems and microservices.

Non-functional Practice:

Maintain clear code, system and process documentation, and develop reliable automated tests using frameworks such as PyTest, Jest or Playwright. Follow and promote good engineering practices, addressing security risks, performance bottlenecks and reliability issues within the systems you work on. Build and maintain services in AWS, using Lambda, RDS, S3 or Lightsail as appropriate to the product. Apply your understanding of AI-related cost, latency and reliability to implementation decisions, including recognising when a deterministic approach is more suitable.

Where you have relevant experience, contribute to infrastructure managed through Terraform, CI/CD workflows using Git Hub Actions, and SQL-first database migrations using tools such as dbmate. Support event-driven processing, containerised Lambda functions, presigned URL uploads and asynchronous validation where these patterns are used.

Learning & Continuous Improvement:

Develop your technical skills through feedback, practical delivery and knowledge sharing, taking an active interest in developments across software engineering and AI. Build your understanding of the sectors YAGRO serves, the problems customers face and how users interact with our products. Explore relevant approaches with senior engineers, drawing on any experience of vector search, embeddings, RAG, fine-tuning, prompt engineering or AI orchestration frameworks such as Lang Chain.

Help evaluate model output quality through structured examples and lightweight evaluation sets. Where relevant, develop your knowledge of custom agent and pipeline tooling, data-processing libraries such as Polars or pandas, and columnar or Parquet-based storage, assessing their usefulness against the problem being solved.

Product & Business Understanding:

Align your work with YAGRO’s business objectives and customer needs,…

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