At a Glance
- Tasks: Join us to build innovative AI solutions and shape the future of procurement.
- Company: Prolo, a dynamic startup revolutionising the construction industry with AI.
- Benefits: Enjoy a hybrid work environment, competitive equity, and access to cutting-edge tech.
- Other info: Be part of a small, agile team with excellent growth opportunities.
- Why this job: Make a real impact by contributing to groundbreaking AI projects in a collaborative team.
- Qualifications: 5+ years in software development, strong Python skills, and a passion for AI.
The predicted salary is between 60000 - 80000 £ per year.
We are seeking a Full-Stack Engineer to join our team and help build the next generation of AI solutions. This is a unique opportunity to be a key technical contributor in a fast-paced, innovative environment where you'll wear many hats and have significant impact on our product and engineering culture.
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.
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. Our stack includes:
- 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: Terraform, GitHub Actions, Helm, Infrastructure-as-Code
- Data Science: Graph analytics, data pipelines, ETL workflows, Jupyter notebooks
Required Qualifications
- 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 event-driven architectures and message queues
- 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
DevOps & Infrastructure
- Hands-on experience with cloud platforms (AWS preferred)
- Experience with containerisation (Docker) and orchestration (Kubernetes)
- Knowledge of Infrastructure as Code (Terraform, CloudFormation, or similar)
- Experience setting up CI/CD pipelines
- 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
- Experience integrating LLM APIs (OpenAI, Anthropic, Gemini, or open-source equivalents) into production applications
- Understanding of core LLM concepts: context windows, token limits, temperature, system prompts, and model selection trade-offs
- Experience with prompt engineering techniques — few-shot prompting, chain-of-thought, structured output, and instruction tuning
Soft Skills
- Wearer of Many Hats: Comfortable switching contexts and working across different domains
- Self-Starter: Ability to work independently and take ownership of projects
- Problem Solver: Strong analytical and debugging skills
- Collaborative: Excellent communication skills and ability to work in a small team
- Adaptable: Comfortable with ambiguity and rapid iteration
Nice-to-Have Qualifications
- Experience with observability tools (OpenTelemetry, Prometheus, Grafana)
- Familiarity with agentic coding workflows — using AI agents to scaffold, refactor, test, and document code autonomously
- Experience with FastAPI or similar async Python web frameworks
- Experience with Neo4j or other graph databases
- Experience with graph algorithms and network analysis
- Experience with Helm and Kubernetes operators
- Background in data science, statistics, or scientific computing
- Experience with graph analytics or network analysis
- Experience with RAG, LLM Orchestration and MCP
- Experience in early-stage startups
What We Offer
- Impact: Direct influence on product direction and technical decisions
- Growth: Opportunity to work across the entire stack and learn new technologies
- Ownership: Take ownership of features from conception to deployment
- Flexibility: Hybrid, remote-friendly work environment
- Equity: Meaningful equity stake in the company
- Learning: Access to cutting-edge technologies and challenging problems
Note: Prolo is a startup with a small engineering team, which means you'll be expected to be versatile, proactive, and comfortable with ambiguity. 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 Developer Hybrid/Remote Working in London employer: Prolo
Prolo is an exceptional employer for Full Stack Developers, offering a dynamic hybrid and remote working environment that fosters innovation and collaboration. With a strong emphasis on employee growth, you'll have the opportunity to work with cutting-edge AI technologies while taking ownership of impactful projects, all within a supportive culture that values versatility and proactive problem-solving.
StudySmarter Expert Advice🤫
We think this is how you could land Full Stack Developer Hybrid/Remote Working in London
✨Tip Number 1
Network like a pro! Reach out to folks in your industry on LinkedIn or at meetups. A personal connection can often get you a foot in the door faster than any application.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those that align with the tech stack mentioned in the job description. This gives potential employers a taste of what you can do.
✨Tip Number 3
Prepare for interviews by practising common technical questions and coding challenges. Use platforms like LeetCode or HackerRank to sharpen your skills and boost your confidence.
✨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, it shows you’re genuinely interested in joining our team.
We think you need these skills to ace Full Stack Developer Hybrid/Remote Working in London
Some tips for your application 🫡
Tailor Your Application:Make sure to customise your CV and cover letter for the Full Stack Developer role. Highlight your experience with Python, async programming, and any relevant projects that showcase your skills in building micro-services and RESTful APIs.
Show Off Your Tech Stack Knowledge:We want to see your familiarity with our tech stack! Mention your experience with AWS, Neo4j, and any AI/ML tools you've used. This will show us you're ready to dive into our projects and contribute from day one.
Be Yourself:Let your personality shine through in your application. We value collaboration and adaptability, so share examples of how you've worked in teams or tackled challenges in a fast-paced environment. It helps us get to know you better!
Apply Through Our Website:Don't forget to submit your application through our website! It's the best way for us to receive your details and ensures you’re considered for the role. Plus, it shows you're keen on joining our team at Prolo!
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 AWS. Brush up on your knowledge of graph databases like Neo4j and be ready to discuss how you've used these tools in past projects.
✨Showcase Your Problem-Solving Skills
Prepare to discuss specific challenges you've faced in previous roles and how you tackled them. Use the STAR method (Situation, Task, Action, Result) to structure your answers, focusing on your analytical and debugging skills.
✨Demonstrate Your Adaptability
Since this role requires wearing many hats, be ready to share examples of how you've successfully switched contexts or worked across different domains. Highlight your ability to thrive in ambiguous situations and your willingness to learn new technologies.
✨Engage with AI Concepts
Given the focus on AI solutions, brush up on your understanding of LLM concepts and prompt engineering techniques. Be prepared to discuss how you've integrated AI into your development process and any tools you've used, like GitHub Copilot.
