Full Stack Software Engineer

We are looking for a deeply passionate, fast-learning Full-Stack Software Engineer to join our engineering team: designing, building, and deploying resilient, scalable web applications for our diverse client base. You will own the technical execution end-to-end; taking ambiguous client needs and turning them into robust, production-ready software across the full stack. If you're not scared to use AI to accelerate your own work and ours, and you thrive on tackling ambiguity across different client ecosystems, this role is for you.

Key Responsibilities

Solution Design & Ownership: Independently design and implement scalable, production-ready applications; front-end, back-end APIs, and data storage, etc…

Technology Stack: Apply expert-level knowledge across modern JavaScript frameworks (React, Vue, Angular), microservices, cloud platforms (like GCP, AWS, OCI, or Azure), and performance-optimised databases.

Quality & DevOps Champion: Establish best practices for clean code, comprehensive testing (unit, integration, E2E), security, and CI/CD, driving an always-shippable product.

Customer-Centric Solutioning: Translate complex business requirements into simple, intuitive software experiences that clearly solve the problem.

Strategic Reusability: Architect with modularity and componentisation in mind, building frameworks and patterns that can be rapidly tailored for new clients across sectors.

Advanced Prototyping: Lead research and prototyping of complex features; real-time data integration, highly interactive UIs.

AI-Accelerated Engineering: Use AI coding tools (e.g., Claude Code) to move faster; generating boilerplate, debugging, writing tests, and documentation while staying deliberate about where human review and judgment must take over.

Cross-Functional Partnership: Collaborate closely with product, UX/UI, and business stakeholders to ensure successful technical definition and delivery of end-to-end solutions.

Knowledge Sharing: Document technical designs, share best practices, and raise the engineering quality bar across the engineering team.

What We’re Looking For

Core Expertise

Full-Stack Acumen: Expert-level proficiency in a modern front-end framework (React/ReactNative) and a back-end environment (Node.js/Express, Java Spring Boot, Python, etc.).

Cloud & DevOps Mastery: Significant hands-on experience architecting and deploying on a major cloud platform (like GCP, AWS, OCI, or Azure), with proven CI/CD, monitoring, and containerisation (Docker) expertise.

Data & Infrastructure: Hands-on expertise with relational and/or NoSQL databases; familiarity with serverless functions, application gateways, and networking. Infrastructure-as-Code (IaC); for example Terraform, experience is a plus.

End-to-End Delivery: A track record of taking applications from concept through to live production, with an unwavering focus on reliability and performance.

Problem-Solving & Communication

Ownership & Ambiguity: Proven ability to take highly ambiguous business problems and translate them into well-defined, delivered technical solutions.

Communication: Exceptional ability to explain complex architectural decisions to both technical and non-technical audiences.

Team Player: Transparent and communicative, anticipating roadblocks and prioritising the team’s success over individual credit.

Continuous Learning: A strong bias for fast, self-directed learning and staying current with new frameworks and best practices.

Nice-to-Haves

Data Engineering Skills: Experience with data pipelines, ETL/ELT processes, or working with large-scale/streaming data.

AI Tooling & Workflows: Practical experience building AI-powered features (e.g., using the Claude API or similar), not just using AI as a coding assistant. Including prompt design, tool use, function calling, and evaluating model outputs in production.

Experience across multiple cloud platforms (GCP, AWS, Azure, OCI).

Experience contributing to reusable internal frameworks or libraries deployed across multiple clients.

What Success Looks Like in Year 1

First 90 Days: Get up to speed on our stack and delivery model, ship your first production grade feature or integration for a client.

6 Months: Become a trusted technical anchor on your project team, contributing to architecture decisions and code review with confidence.

1 Year: Drive measurable improvements in delivery speed and quality through reusable patterns, AI-accelerated workflows, etc.