We are looking for a highly skilled Senior 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, containerized 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
-
6+ years of backend development experience.
-
4+ years of hands-on experience with Python.
-
2+ years of production experience with Go (Golang).
-
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 optimization 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.
