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AI Summary

You will build and evolve web applications and service layers for real-time data processing platforms using modern full-stack technologies. Additionally, you will collaborate with senior engineers to develop GenAI-facing product surfaces and integrate AI coding agents into the development lifecycle.

Job Overview

As a Full-Stack Engineer within our Product Development team, you will help build and evolve the web applications and service layers that sit on top of our real-time data processing, integration, and decisioning platforms targeting K8, cloud and big data environments.

We are looking for an early-career developer who thrives in a fast-paced, start-up environment and is eager to take ownership of meaningful features early on. You will work across the stack — building REST APIs and services, and the front ends that consume them — on products that process hundreds of billions of events per day for enterprise customers. You will touch React/TypeScript single-page applications, Python and FastAPI services, JVM-backed platform APIs, relational databases, charting and dashboarding, authentication and role-based access control, and messaging-platform integrations across Slack, Microsoft Teams and WhatsApp.

You will also work on GenAI-facing product surfaces — streaming LLM chat over governed data, tool calling through the Model Context Protocol (MCP), and metadata enrichment pipelines — collaborating with senior engineers to take these from prototype to production.

Critically, this is an AI-native engineering team. Our repositories are structured to be worked on with AI coding agents: architecture and convention files that agents read directly, and custom skills that drive the ticket lifecycle from analysis through execution to documentation. We expect you to be genuinely effective with these tools, and fully accountable for the code you ship with them. Candidates should be familiar with emerging technologies such as Generative AI and LLM-based assistants, and eager to learn distributed systems from the people who build them.

Requirements:

  • BS in Computer Science or equivalent, or demonstrable equivalent experience.
  • 0–2 years experience building web applications, with shipped work you can walk us through.
  • Solid programming fundamentals — data structures, algorithms, and object-oriented programming — and the ability to reason about correctness before reaching for a debugger.
  • Proficiency in Python and JavaScript.
  • Hands-on experience with a modern front-end framework (React preferred) as well as core web fundamentals: DOM, fetch, ES modules, HTML and CSS written by hand.
  • Experience building and consuming REST APIs.
  • Working knowledge of SQL and relational data modelling.
  • Experience with AI coding assistants (e.g. Claude Code, GitHub Copilot, Cursor, ChatGPT) — and the ability to use them effectively for accelerated development while maintaining code quality and design rigor. You must be able to explain, defend and debug every line you ship, whether you or an agent typed it, and to recognise plausible-but-incorrect generated code before it reaches review.
  • Able to develop and troubleshoot in a Linux environment.
  • Familiarity with Git and collaborative code review.
  • Ability to work with a distributed team following Agile methodologies.
  • Excellent communication, interpersonal, and problem-solving skills, must be a team player. Much of this role involves writing precise specifications and instructions for both humans and AI agents.


Preferred Qualifications:

  • Experience with TypeScript, Next.js, Redux, or Material-UI.
  • Experience with FastAPI, Pydantic, or asynchronous Python.
  • Exposure to LLM APIs, prompt engineering, context management, tool calling, MCP, RAG, or agent frameworks.
  • Experience with data visualisation libraries (ECharts, ApexCharts, D3, Plotly).
  • Experience with Docker and Kubernetes.
  • Experience with automated testing frameworks (pytest, Playwright, Cypress, Jest).
  • Exposure to Java or Scala, or willingness to learn — significant parts of our platform are JVM-based.
  • Exposure to authentication, RBAC, or multi-tenant permission models.
  • Experience with Cloud services from AWS/Google/Azure.
  • Exposure to big data or streaming technologies (Kafka, Spark, HDFS).
  • Experience with NoSQL databases.
  • Contributions to open source.
  • Jupyter, pandas, or numpy for data exploration.

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