Senior Software Engineer (Python) AI Platform & Distributed Systems

As a highly skilled Backend Engineer with a strong background in Python, system design, and infrastructure, you will join our team to design, build, and maintain scalable backend systems. Your role will involve collaborating with cross-functional teams to deliver robust and efficient solutions. You will think end-to-end, from designing high-level architecture to ensuring production-grade reliability and performance. Key Responsibilities: - Develop and maintain backend services and APIs using Python & NodeJs. - Design scalable, resilient, and maintainable systems focusing on system architecture and distributed systems. - Integrate AI and large language models (LLMs) into applications with a focus on performance, scalability, and cost-efficiency. - Collaborate with AI/ML teams to deploy models into production pipelines. - Optimize infrastructure for AI workloads such as GPU usage, caching, and batch processing. - Build and maintain monitoring, logging, and observability for AI-powered systems. - Troubleshoot and resolve issues in production systems while ensuring high reliability. - Participate in design and code reviews and drive engineering best practices across the team. - Automate deployment pipelines for backend and AI services (CI/CD, IaC). Required Skills & Qualifications: - Strong experience in Python (FastAPI, Flask, Django, or similar) or NodeJS (Express, Fastify, or similar). - Solid understanding of system design principles including scalability, fault tolerance, and distributed systems. - Experience with infrastructure and DevOps tools like Docker, Kubernetes, Terraform, and CI/CD pipelines. - Hands-on experience with cloud platforms (AWS, Azure, GCP), especially for AI workloads. - Knowledge of databases (SQL & NoSQL) and caching systems (Redis, Memcached). - Experience integrating LLMs or AI APIs into production systems (OpenAI, HuggingFace, LangChain, etc.). - Familiarity with messaging/streaming systems like Kafka, RabbitMQ. - Monitoring and observability experience with tools like Prometheus, Grafana, ELK. - Strong problem-solving, debugging, and analytical skills. - Excellent communication and collaboration skills. Nice to Have: - Experience with generative AI pipelines, vector databases, and embeddings. - Familiarity with ML Ops tools (MLflow, BentoML, Ray Serve, etc.). - Knowledge of event-driven architectures and microservices. - Prior experience in AI/LLM-focused startups or high-scale AI systems. In addition to the exciting technical challenges and opportunities for growth, we offer a collaborative team culture with a focus on learning and innovation, competitive compensation, and growth opportunities.,