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- Tasks: Build AI solutions and scale micro-services for a cutting-edge procurement platform.
- Company: Join an innovative tech company transforming the construction industry with AI.
- Benefits: Enjoy competitive salary, remote work options, and opportunities for professional growth.
- Other info: Mentorship opportunities and a hybrid work culture await you!
- Why this job: Make a real impact by developing intelligent systems in a dynamic environment.
- Qualifications: 5+ years in software engineering, strong Python skills, and experience with cloud platforms.
The predicted salary is between 60000 - 80000 £ per year.
We are seeking a Senior Full-Stack Engineer to join our team and help build the next generation of AI solutions. As a full-stack engineer, you'll work across the entire technology stack—from backend services and data pipelines to infrastructure and deployment. You'll collaborate closely with the engineering team to architect, build, and scale our micro-services based platform while maintaining high code quality and operational excellence, utilising AI to maximise software development productivity.
Prolo is building an AI-powered procurement platform for the construction industry, which is one of the oldest and least digitised sectors in the world. The core system ingests unstructured purchase orders and transforms them into structured materials data, integrating with a network of suppliers and logistics partners to automate quoting, sourcing, and fulfilment workflows.
What We're Building: We're building a sophisticated AI platform that leverages graph databases, machine learning, and modern cloud infrastructure to deliver intelligent procurement and customer service solutions.
- Backend Services: Python 3.13, FastAPI, async micro-services architecture
- Data Layer: Neo4j graph database, PostgreSQL, complex data modelling
- AI/ML: OpenAI integration, semantic search, conversational agents, unstructured data analysis and extraction
- Infrastructure: AWS (Lambda, ECS/EKS, API Gateway, S3)
- DevOps: Data Science: Graph analytics, data pipelines, ETL workflows, Jupyter notebooks
Software Development:
- ~5+ years of professional software engineering experience
- Strong proficiency in Python (3.10+) with deep understanding of async programming
- Experience with Poetry or similar Python dependency management tools
- Experience building RESTful APIs and micro-services
- Solid understanding of database design and optimisation (both SQL and NoSQL)
- Experience with graph databases (Neo4j preferred) or willingness to learn quickly
- Knowledge of API design principles, data validation, and serialisation
- Experience with AWS Lambda and serverless architectures
- Experience working across the stack (backend + some frontend)
- Understanding of web technologies, and API integrations
- Ability to contribute to responsive frontend code when needed
- Hands-on experience using AI-assisted development tools (e.g. Cursor, GitHub Copilot) including prompt engineering, context management, and evaluating AI-generated code critically
- Familiarity with agentic coding workflows — using AI agents to scaffold, refactor, test, and document code autonomously
DevOps & Infrastructure:
- Hands-on experience with cloud platforms (AWS preferred)
- Understanding of service deployment, monitoring, and troubleshooting
Data Science/Analytics:
- Experience with data analysis using Python (pandas, numpy)
- Understanding of data pipelines and ETL processes
AI/LLM Engineering:
- Understanding of core LLM concepts: context windows, token limits, temperature, system prompts, and model selection trade-offs
- Experience designing and building agentic systems — tool-calling agents, multi-step reasoning, and human-in-the-loop workflows
- Understanding of MCP (Model Context Protocol) or similar standards for connecting AI models to external tools and data sources
- Awareness of responsible AI practices: bias, safety, output validation, and guardrails in production systems
- Quality trade-offs in real deployments
Ability to work independently and take ownership of projects. Mentoring: Able to mentor less-experienced Software Engineers.
Experience with FastAPI or similar async Python web frameworks. Experience with Neo4j or other graph databases. Experience with graph algorithms and network analysis. Background in data science, statistics, or scientific computing. Experience with graph analytics or network analysis.
Growth: Opportunity to work across the entire stack and learn new technologies.
Ownership: Take ownership of features from conception to deployment.
Hybrid, remote-friendly work environment. Any relevant projects or work that demonstrates your experience. Experience building scalable backend systems. Ability to work across multiple domains (backend, DevOps, data). Examples of taking projects from idea to production. Contributions to open source or personal projects.
If you're excited about building something from the ground up and working across the entire technology stack, we'd love to hear from you.
Full Stack Engineer/Agile Engineer in City of London employer: Prolo
Contact Detail:
Prolo Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Full Stack Engineer/Agile Engineer in City of London
✨Tip Number 1
Network like a pro! Reach out to your connections in the tech industry, especially those who work with AI or full-stack development. A friendly chat can lead to insider info about job openings that aren't even advertised yet.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving Python, micro-services, or AI. This gives potential employers a taste of what you can do and sets you apart from the crowd.
✨Tip Number 3
Prepare for technical interviews by brushing up on your coding skills and understanding of async programming. Practice common algorithms and data structures, and be ready to discuss your experience with AWS and graph databases.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, we love seeing candidates who are genuinely interested in joining our team!
We think you need these skills to ace Full Stack Engineer/Agile Engineer in City of London
Some tips for your application 🫡
Tailor Your CV: Make sure your CV reflects the skills and experiences that match the job description. Highlight your proficiency in Python, experience with micro-services, and any relevant projects you've worked on. We want to see how you can contribute to our AI-powered procurement platform!
Craft a Compelling Cover Letter: Your cover letter is your chance to show us your personality and passion for the role. Explain why you're excited about building AI solutions for the construction industry and how your background makes you a great fit for our team. Keep it engaging and authentic!
Showcase Your Projects: If you've got any personal or open-source projects that demonstrate your skills, don’t hold back! Share links to your GitHub or any other platforms where we can see your work. We love seeing practical applications of your coding prowess!
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it shows us you’re keen on joining our team at StudySmarter!
How to prepare for a job interview at Prolo
✨Know Your Tech Stack
Make sure you’re well-versed in the technologies mentioned in the job description, especially Python, FastAPI, and Neo4j. Brush up on async programming and be ready to discuss how you've used these tools in past projects.
✨Showcase Your Projects
Prepare to talk about specific projects where you've taken ownership from conception to deployment. Highlight any experience with AI-assisted development tools and how they’ve improved your workflow.
✨Understand the Business Context
Familiarise yourself with the construction industry and the challenges it faces regarding procurement. Being able to discuss how your skills can help solve these issues will set you apart.
✨Ask Insightful Questions
Prepare thoughtful questions about the team’s current projects, their use of AI, and how they envision the future of their platform. This shows your genuine interest and helps you assess if the company is the right fit for you.