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Socket.dev is seeking a seasoned Python Backend Engineer to join our development team in building and maintaining server-side logic. You will connect the application with third-party services and support frontend integration with the Python application.
The ideal candidate brings 10+ years of backend experience, deep Python expertise, and mastery of REST APIs, distributed systems, and containerization with Docker and Kubernetes.
We are looking for a skilled Python Backend Engineer to join our development team. In this role, you will be responsible for building and maintaining the server-side logic. You will be tasked with developing back-end components, connecting the application with third-party web services, and supporting the front-end developers by integrating their work with the Python application. Our ideal candidate must have demonstrated expertise in Python. Knowledge of Data Engineering & ML domain & training lifecycle is an added plus. You are comfortable with analyzing business requirements, identifying gaps, and translating requirements into technical designs. You are proficient and adhere to the best practices of software development, such as agile development, code reviews, continuous integration, and automated testing. You have worked closely with project managers, UI/UX designers, and other cross functional stakeholders to deliver high quality work on-time. You are well-versed in GenAI tools and agentic development, with hands-on experience building or integrating LLM-powered workflows, AI agents, and modern AI-assisted development practices.
Bachelor's degree in Computer Science or related field. 10+ years of extensive backend development experience, with solid foundational programming skills (algorithms, data structures, OOP, etc) and experience designing, writing, reviewing, testing and delivering software for applications and systems at scale. Expertise in architecting and developing backend systems using Python; extensive experience in FastAPI, Django, or Flask will be great. Proficient in REST API, Redis, VectorDB or other large scale data storage systems. In-depth knowledge of workflow orchestration systems like Airflow, distributed systems, cloud-native applications, and containerization technologies like Docker and Kubernetes.
Experience in Data Engineering & ML domain & training lifecycle. Experience with large-scale data processing, distributed systems , microservices, various caching strategies, and performance optimization. Excellent problem solving skills and be able to navigate through complex technical challenges and design decisions. Experience with cloud platforms like AWS or GCP Experience building and productionizing GenAI applications, including LLM integration, prompt engineering, RAG pipelines, and agentic workflows using frameworks such as LangChain or similar tools. Master or Ph.D. in a related field. Previous experience in a high-growth tech company or similar environment.