Pansophic Technologies

Location: Mohali, India (Full-time Onsite) Experience Required: 7–8+ years Openings: 1 Role Overview We are looking for a Senior Python Developer to lead core engineering efforts for our AI infrastructure, internal services, and enterprise-grade applications. You will design and build scalable, secure, and performant backend systems , and work closely with AI engineers, DevOps, and product teams to bring our platform features to life. This is a technical leadership role with substantial ownership and impact across our backend architecture. Key Responsibilities Design, implement, and optimize modular, scalable Python-based services . Own backend architecture for services supporting AI pipelines, user management, job queues, model execution, and system orchestration. Build robust integrations with external APIs, databases (SQL/NoSQL), file systems, and cloud components. Lead discussions on software design, code structure, architecture, and best practices . Contribute to DevOps pipelines, containerization (Docker), and deployment workflows (CI/CD). Collaborate with AI teams to interface model logic, APIs, toolchains , and data layers effectively. Review code, mentor junior developers, and uphold high engineering standards. Maintain a focus on performance, security, and reliability in production environments. Minimum Qualifications 7–8+ years of experience as a Python developer, with production-grade backend ex perience.Exper tise in:Pytho n 3.x, inc luding asynchronous programming (asyncio, FastAPI, Celery)Frame works such as FastA PI, Fla sk , Dja ng o, or custom microservicesREST APIs and JSON-based communicationStron g database knowledge (PostgreSQL, MongoDB, Redis, or similar).Exper ience working with conta inerized applications usin g Docker.Solid understanding of API s ecurity, authentication (OAuth2, JWT), and role-based access controls.Profi cient with Git, CI/CD tools, and Linux-based development environments. Preferred Qualifications Familiarity with AI model integration , vector search systems (e.g. FAISS, Weaviate), or ML workflow orchestration is a plus. Experience working with message brokers like RabbitMQ or Kafka. Exposure to cloud platforms such as AWS/GCP, and infrastructure-as-code tools like Terraform. Knowledge of MCP (Model Context Protocol) or similar architectural standards for managing modular AI flows is a strong advantage. Prior experience in AI-driven or data-heavy platforms is a major bonus.