About the role
Requirements:
- Experience: 5+ years in software development, systems integration, or platform engineering. Customer-facing experience is a plus.
- Background: Bachelor's or Master's degree in Computer Science, Engineering, or a related technical field.
- Coding Skills: Strong proficiency in TypeScript/JavaScript, Python, data structures and algorithms. (Nice to have: Go)
- Applied AI Knowledge: Familiarity with large language models (LLMs), prompt engineering, frameworks like RAG and function calling, and building evals to validate agentic AI solutions.
- Integration Expertise: Deep experience with large-scale data synchronisation (one-way and two-way), API integration patterns (REST, GraphQL, webhooks), and event-driven/pub/sub architectures
- Cloud and Deployment: Hands-on experience deploying on serverless and edge platforms (AWS Lambda, Google Cloud Functions) with modern DevOps practices (CI/CD, containers, observability).
- Data Transformation: Skilled in data mapping, schema alignment, and working with heterogeneous systems. Understanding of data modelling and graph data structures.
- Observability: Experience implementing clear logging, actionable error surfacing, and telemetry to support faster debugging and issue resolution.
- Context-Aware Systems: Familiarity with Model Context Programming (MCP) for building adaptive, context-aware integrations.
- Problem-Solving: Strong track record of triaging and unblocking both technical and non-technical blockers to keep projects moving forward.
- Documentation: Experience writing concise, well-structured documentation that supports long-term team understanding and seamless onboarding.
- Communication: Strong written and verbal skills to articulate technical concepts to engineers, product teams, and business stakeholders.