We are looking for a highly skilled Backend Developer who can design, build, and scale distributed systems that power high-growth products and AI driven applications.
The ideal candidate has deep expertise in Python and Go, extensive experience with FastAPI, containerised deployments using Docker and Kubernetes, and a proven track record of scaling systems serving millions of requests while maintaining reliability, performance, and security.
This role requires strong architectural thinking, hands-on coding expertise, and the ability to optimize backend systems for high throughput, low latency, and cost efficiency.
Key Responsibilities:
Backend Architecture & Development
- Design and develop highly scalable backend services using Python and Go.
- Build and maintain RESTful APIs and microservices using FastAPI.
- Architect distributed systems capable of handling high traffic and large-scale workloads.
- Write clean, maintainable, testable, and production-grade code.
- Establish engineering standards, code review practices, and backend best practices.
Performance & Scalability:
- Lead initiatives for system scalability, reliability, and performance optimization.
- Identify and eliminate bottlenecks in APIs, databases, caching layers, and infrastructure.
- Optimize application latency, throughput, and resource utilization.
- Design systems for horizontal scaling and fault tolerance.
- Implement caching strategies using Redis and distributed caching mechanisms.
Cloud & Infrastructure:
- Build and manage containerized applications using Docker.
- Deploy, operate, and optimize workloads on Kubernetes clusters.
- Design CI/CD pipelines and automated deployment workflows.
- Implement infrastructure observability using monitoring, logging, and tracing tools.
- Drive cloud cost optimization and infrastructure efficiency initiatives.
AI Platform Development:
- Develop backend services supporting AI/ML applications and LLM-based products.
- Build APIs for AI model inference, orchestration, and integration.
- Work with vector databases, embeddings, RAG architectures, and model-serving pipelines.
- Optimize AI workloads for performance, scalability, and cost.
- Collaborate with AI engineers and data scientists to productionize machine learning systems.
Reliability & Security:
- Design resilient systems with high availability and disaster recovery considerations.
- Implement authentication, authorization, and API security best practices.
- Ensure compliance with security standards and data protection requirements.
- Conduct architecture reviews and proactively address technical debt.
Required Qualifications:
- 2+ years of backend development experience.
- Hands-on experience with Python/GO.
- Strong expertise in FastAPI and modern API design principles.
- Proven experience scaling applications from startup scale to high-traffic production environments.
- Extensive experience with Docker and Kubernetes in production.
- Strong understanding of distributed systems, microservices architecture, and event-driven systems.
- Deep knowledge of database optimization and query performance tuning.
- Experience with PostgreSQL, MySQL, MongoDB, Redis, or similar technologies.
- Strong understanding of concurrency, parallel processing, and asynchronous programming.
- Strong debugging, profiling, and performance optimisation skills.
Preferred Qualifications:
- Experience building AI-powered products or Generative AI applications.
- Hands-on experience with:
- LLM integrations (OpenAI, Anthropic, Gemini, etc.)
- RAG architectures
- Vector databases (Pinecone, Weaviate, Qdrant, Milvus)
- AI orchestration frameworks (LangChain, LlamaIndex)
- Experience with message queues such as Kafka, RabbitMQ, or NATS.
- Experience with cloud platforms (AWS, GCP, Azure).
- Knowledge of Infrastructure as Code (Terraform, Pulumi).
- Experience with service mesh technologies and Kubernetes operators.
- Exposure to MLOps and AI deployment workflows.
