Mid Software Engineer

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. Job requirements

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…