Backend Engineer
New
E
EDITEDRetail Intelligence
Our flexible working options—including hybrid working, flexible hours and a work from anywhere policy—empower our team to perform at their best.Full-TimeSenior
Salary not disclosed
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Job Details
- Experience
- 5+ years
- Required Skills
- AWSPythonDjangoElasticSearchFlaskMachine LearningFastAPIRESTful APIsDevOps
Requirements
- 5+ years of experience in back-end engineering roles, with a track record of delivering complex projects and demonstrating technical leadership in a senior position.
- Proven ability to take ownership of projects, drive results, and mentor team members to achieve success.
- Proficiency in Python and fluent in some *nix flavour.
- Excellent communication skills, with the ability to articulate technical concepts to both technical and non-technical stakeholders.
- Strong understanding of data management, APIs, and infrastructure, with the ability to architect scalable solutions.
- Ability to adapt and learn new technologies quickly, with a passion for ensuring your code is maintainable, driven by a hands-on curiosity about AI.
- Hands-on experience building with LLMs - agents, RAG, evals and tooling such as MCP (desirable).
- An active interest in DevOps and Machine Learning (desirable).
- Experience with frameworks like Django, Flask or FastAPI, Elasticsearch or similar NoSQL technologies, and relational databases (desirable).
- Experience with large-scale data processing, including self-hosted or bare-metal environments (desirable).
Responsibilities
- Collaborate with cross-functional teams, including Product Managers, Data Scientists, Retail Analysts and Customer Success, to understand business requirements, identify problems, and develop innovative solutions.
- Build our AI chatbot, along with the agents, tooling and MCP integrations behind it - used both internally and by customers.
- Lead by example on how we build with AI, while raising the bar on code quality, testing and observability through review and mentoring.
- Scale and adapt our large-scale retail data infrastructure, spanning AWS and bare metal, as the demands of AI-driven products reshape our technical architecture.
- Own what you build end to end, from scoping the problem through to deploying, monitoring and iterating on it in production.
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