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 opportunities for growth.
- Other info: Be part of a small, agile team where your contributions truly matter.
- Why this job: Make a real impact by working on cutting-edge technology 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 Senior 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
- 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 observability tools (OpenTelemetry, Prometheus, Grafana)
- 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)
- 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
- Practical knowledge of RAG (Retrieval-Augmented Generation) architectures, including chunking strategies, vector embeddings, and similarity search
- Familiarity with LLM orchestration frameworks such as LangChain, LlamaIndex, or similar
- 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
- Knowledge of LLM evaluation methods — measuring accuracy, hallucination, latency, and cost
- Awareness of responsible AI practices: bias, safety, output validation, and guardrails in production systems
- Experience managing LLM costs and optimising for latency vs. quality trade-offs in real deployments
Soft Skills
- Comfortable switching contexts and working across different domains
- Ability to work independently and take ownership of projects
- Strong analytical and debugging skills
- Excellent communication skills and ability to work in a small team
- Comfortable with ambiguity and rapid iteration
- Able to mentor less-experienced Software Engineers
Nice-to-Have Qualifications
- 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 Apple and Google App Stores
- Experience in early-stage startups
What We Offer
- Direct influence on product direction and technical decisions
- Opportunity to work across the entire stack and learn new technologies
- Take ownership of features from conception to deployment
- Hybrid, remote-friendly work environment
- Meaningful equity stake in the company
- Access to cutting-edge technologies and challenging problems
How to Apply
Please submit your resume/CV, a brief cover letter explaining why you’re interested in this role, links to your GitHub profile or relevant code samples, and any relevant projects or work that demonstrates your experience. We’re particularly interested in candidates who can demonstrate experience building scalable backend systems, ability to work across multiple domains (backend, DevOps, data), examples of taking projects from idea to production, and contributions to open source or personal projects.
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.
Senior Full Stack Engineer in London employer: Prolo
Prolo is an exceptional employer for Senior Full Stack Engineers, offering a dynamic and innovative work environment where your contributions directly shape the future of AI solutions in the construction industry. With a strong emphasis on employee growth, you will have the opportunity to work across the entire technology stack, engage with cutting-edge technologies, and take ownership of impactful projects, all while enjoying a flexible, hybrid work culture that values collaboration and creativity.
StudySmarter Expert Advice🤫
We think this is how you could land Senior Full Stack Engineer in London
✨Tip Number 1
Network like a pro! Reach out to your connections in the industry, attend meetups, and engage with online communities. You never know who might have the inside scoop on job openings or can refer you directly.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those that highlight your full-stack capabilities. Make sure to include links to your GitHub profile and any relevant code samples when applying through our website.
✨Tip Number 3
Prepare for technical interviews by brushing up on your coding skills and system design knowledge. Practice common algorithms and data structures, and be ready to discuss your past projects and how you tackled challenges.
✨Tip Number 4
Be proactive! Follow up after interviews with a thank-you note expressing your enthusiasm for the role. It shows you're genuinely interested and keeps you top of mind for the hiring team.
We think you need these skills to ace Senior Full Stack Engineer in London
Some tips for your application 🫡
Craft a Tailored Cover Letter:When writing your cover letter, make sure to highlight your passion for AI solutions and how your experience aligns with our tech stack. We want to see your personality shine through, so don’t be afraid to let us know why you’re excited about this role!
Showcase Your Projects:Include links to your GitHub profile or any relevant code samples that demonstrate your skills. We love seeing real-world applications of your work, so share projects that showcase your ability to build scalable systems and work across different domains.
Be Clear and Concise:Keep your resume and cover letter clear and to the point. We appreciate straightforward communication, so avoid jargon and focus on what makes you a great fit for the Senior Full Stack Engineer role. Remember, less is often more!
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 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 Neo4j. Brush up on your knowledge of async programming and micro-services architecture, as these will likely come up during technical discussions.
✨Showcase Your Projects
Prepare to discuss specific projects where you've built scalable backend systems or worked across multiple domains. Bring examples that highlight your experience with AI integration, data pipelines, and any contributions to open source or personal projects.
✨Demonstrate Problem-Solving Skills
Be ready to tackle some coding challenges or hypothetical scenarios during the interview. Practice explaining your thought process clearly, as this will showcase your analytical skills and ability to debug effectively.
✨Emphasise Collaboration
Since the role involves working closely with a small team, highlight your collaborative experiences. Share examples of how you've communicated effectively, mentored others, or adapted to different roles within a project to demonstrate your versatility.
