Monitor system performance and drive optimisation strategies to maintain platform scalability and reliability.
Uphold security standards and compliance requirements across all technical implementations.
Integrate LLMs and generative AI APIs (AWS Bedrock, OpenAI, Azure OpenAI) and custom models into production applications.
Build RAG architectures and AI application patterns that enable intelligent data processing and automated insight generation.
Partner with the AI Analyst to translate analytical requirements into technical specifications and take proof-of-concepts to production.
Implement prompt engineering and AI workflow orchestration to support automated content generation and data analysis.
Requirements
3–5 years of full-stack development experience building and deploying web applications end-to-end across React/Vue, TypeScript/JavaScript, and Python or Node.js — with a proven ability to build clean, maintainable architectures.
Cloud-native systems proficiency on AWS — Lambda, API Gateway, S3, EC2 — with a solid understanding of serverless design patterns and experience deploying production-grade systems.
Database and API development experience across SQL and NoSQL databases, RESTful API design, and data integration patterns — with the ability to optimise data flows across distributed services.
DevOps experience including CI/CD pipeline implementation, automated testing, and production system monitoring — with a track record of taking prototypes to production reliably and at scale.
Comfortable with Git, Agile engineering practices, and translating ambiguous requirements into practical technical solutions quickly.
Confident communicator — able to engage senior stakeholders, present technical options clearly, and adapt well in fast-moving environments.
AI/ML integration experience with LLMs and generative AI APIs (AWS Bedrock, OpenAI, Azure OpenAI), including working knowledge of RAG patterns and prompt optimisation is a nice to have.
Databricks or equivalent data engineering platform experience, with familiarity of MLOps concepts and model lifecycle management is a nice to have.
Advanced AWS certifications or equivalent cloud platform expertise is a nice to have.
Experience in regulated industries — financial services, gaming, or similar — with an understanding of compliance requirements is a nice to have.
Tech Stack
AWS
Azure
Cloud
EC2
Flutter
JavaScript
Microservices
Node.js
NoSQL
Python
React
SDLC
SQL
TypeScript
Vue.js
Benefits
Hybrid Model: 2 office days/week with flexible leave policies, including maternity, paternity, and sabbaticals.
Access to Learnerbly, Udemy, and a Self-Development Fund for upskilling.
Career growth through Internal Mobility Programs.
Comprehensive Health Insurance for you and dependents.
Customised well-being programmes and a 24/7 helpline for holistic wellness.
Sharesave Plan to purchase discounted company shares.
Volunteering Leave and Team Events to build connections.
Recognition through the Kudos Platform and Referral Rewards.