Role Overview
This role focuses on building a scalable, high-performance AI and ML platform used for workflow automation, data ingestion, model serving, multi-agent orchestration, analytics dashboards, and enterprise deployments. The developer will own end-to-end product modules across frontend, backend, infrastructure, and DevOps while collaborating with AI engineers, product managers, and design teams.
Key Responsibilities
Platform Architecture and Development
- Design and build microservices, APIs, and backend systems for model serving, vector operations, data pipelines, and workflow orchestration.
- Develop frontend interfaces for dashboards, real-time analytics, admin controls, and user management.
- Implement modular, scalable services that support future AI features such as RAG, embeddings, streaming inference, task queues, and evaluation engines.
End-to-End Ownership
- Convert product specs into technical architecture with clean, maintainable code.
- Lead complex feature development, ensure code quality, maintain test coverage, and drive CI/CD excellence.
- Own performance optimisation across services, databases, caching layers, and UI rendering.
Systems Integration
- Integrate with vector databases, LLM endpoints, Python ML microservices, authentication systems, event systems, and third-party APIs.
- Build reliable communication layers between AI models, backend services, and frontend clients.
DevOps and Deployment
- Manage deployments on AWS or Azure; implement autoscaling, containerisation, monitoring, and logging.
- Contribute to infra-automation using Terraform, Docker, Kubernetes, and GitHub Actions.
- Ensure security, data protection standards, and compliance readiness.
Required Skills and Experience
Backend
- Strong proficiency in Node.js, TypeScript, or Python-based backend frameworks.
- Experience building distributed systems, API gateways, model inference services, streaming endpoints, or event-driven architectures.
- Expertise with SQL and NoSQL databases, including PostgreSQL, MongoDB, Redis.
- Understanding of vector stores (Pinecone, Weaviate, Qdrant) and model serving patterns is a plus.
Frontend
- Advanced experience with React, Next.js, modern UI components, and state management.
- Strong skills in building dashboards, workflow builders, visual editors, and complex UI interactions.
- Familiarity with WebSockets, server-side rendering, and performance optimisation.
Cloud and DevOps
- Hands-on experience with Docker, Kubernetes, CI/CD pipelines, and cloud-native services.
- Ability to optimise deployments, manage environments, automate workflows, and implement secure practices.
Engineering Excellence
- Strong understanding of system design, microservices architecture, API lifecycle, scalability, and reliability.
- Excellent debugging skills, code organisation, documentation standards, and testing practices.
- Experience working in fast-paced, product-driven environments.
Preferred Experience
- Worked previously on AI, ML, data engineering, workflow automation, or developer tools.
- Familiar with model serving, fine-tuning workflows, embeddings, and interacting with LLMs.
- Experience with agentic systems, message queues, background workers, and observability stacks.
- Understanding of RBAC, multi-tenant architecture, subscription billing, or SaaS platform engineering.
