Backend Developer

We are seeking a talented Backend Developer with strong expertise in Python and Go (Golang) to build and scale high-performance backend systems. The ideal candidate has experience working on AI/ML-powered products, designing scalable architectures, optimizing system performance, and developing robust APIs and microservices that support large-scale applications. Key Responsibilities Design, develop, and maintain backend services using Python and Go. Build scalable APIs, microservices, and distributed systems for AI-driven applications. Collaborate with AI/ML engineers to integrate machine learning models, LLMs, and AI services into production systems. Architect and implement solutions capable of handling high traffic, large datasets, and real-time processing workloads. Drive performance optimization initiatives across applications, databases, and infrastructure. Improve system scalability, reliability, and fault tolerance through efficient architecture and engineering best practices. Design and optimize data pipelines, caching layers, and asynchronous processing workflows. Monitor, troubleshoot, and resolve production issues while ensuring high system availability. Participate in system design discussions and contribute to technical roadmap decisions. Write clean, maintainable, and well-tested code following industry best practices. Required Qualifications 4+ years of backend development experience. Strong programming skills in Python and Go (Golang). Proven experience building and scaling production-grade applications. Hands-on experience optimizing application performance, database queries, and distributed systems. Experience developing RESTful APIs and microservices. Strong understanding of system design, scalability patterns, and high-availability architectures. Experience working with relational and/or NoSQL databases such as PostgreSQL, MySQL, MongoDB, Redis, or DynamoDB. Knowledge of asynchronous processing, message queues, and event-driven architectures. Familiarity with cloud platforms such as AWS, GCP, or Azure. Experience with Docker, CI/CD pipelines, and containerized deployments. AI/ML Experience (Required) Experience working on at least one AI/ML-powered product or platform. Experience integrating AI services, machine learning models, LLMs, vector databases, or inference pipelines into backend systems. Understanding of AI application architecture, model serving, prompt workflows, RAG systems, or data processing pipelines is highly preferred. Ability to collaborate effectively with Data Science and AI Engineering teams. Preferred Qualifications Experience with FastAPI, gRPC, or similar backend frameworks. Experience with Kubernetes and cloud-native architectures. Familiarity with vector databases, model deployment, and AI infrastructure. Experience with monitoring and observability tools such as Prometheus, Grafana, ELK, or OpenTelemetry. Knowledge of distributed caching and high-throughput data processing systems. Nice to Have Experience with Generative AI, LLM applications, RAG architectures, or AI agents. Exposure to MLOps tools and model deployment workflows. Experience building backend systems supporting real-time AI inference.