We are seeking a talented Backend Software Engineer with a focus on AI/ML to join our team. In this role, you will be responsible for designing, implementing, and maintaining scalable backend services primarily in Python. Your main tasks will involve building and managing data pipelines for AI/ML applications, as well as operationalizing and deploying Generative AI systems for production use.Design, implement, and maintain scalable backend services in PythonBuild and maintain data pipelines for AI/ML applications for production use-casesOperationalize and deploy Generative AI systems (APIs, SDKs, pipelines)Develop APIs to serve AI features to downstream applicationsOrchestrate agentic workflows using frameworks like LangChain, LangGraph, or custom solutionsEnsure monitoring, logging, and observability of GenAI servicesCollaborate cross-functionally to ensure system performance, scalability, and reliabilityNote:This position is ideal for a hands-on software engineer with significant exposure to AI product development, rather than a data science or AI/ML research role.We are looking for individuals who excel in operational excellence, have deployment experience, and possess systems-level thinking for real AI applications.Job requirementsOffer Requirements:5+ years of practical experience as a Python backend developerStrong knowledge of software engineering principles, clean code practices, and testing methodologiesPractical experience with Python backend frameworks: FastAPI (preferred), Flask or DjangoPractical experience with SQL databases and related Python librariesHands-on experience with cloud platforms: Azure (preferred), AWS or GCPExperience designing and implementing scalable backend services (APIs, data pipelines, SDKs, etc.)Practical experience with building and deploying AI-based applications, including LLMs and embedding models (e.g., OpenAI, Anthropic, Hugging Face)Familiarity with Retrieval-Augmented Generation (RAG) based systems, agentic workflows and Generative AI applicationsFamiliarity with containerized development with DockerExperience with data science Python libraries such as pandas, NumPy, Scikit-learnExperience with Python GenAI frameworks (e.g., LangChain, LangGraph) is a plusFamiliarity with CI/CD workflows in GitLab is a plusFamiliarity with monitoring and logging tools (e.g., Prometheus, Grafana) is a plusFamiliarity with gRPC for high-performance service communication is a plusFamiliarity with Model Context Protocol (MCP) is a plusFamiliarity with AI observability and tracing tools (e.g., Langfuse) is a plus
