Lead Software Engineer – Python | Cloud & AI

Аналитика рынка

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Описание

Key Responsibilities Lead the architecture, technical design and implementation of enterprise-scale applications and services. Develop and maintain high-quality backend services using Python and modern backend frameworks . Design and implement scalable REST APIs, microservices and distributed systems. Translate business and product requirements into technical architecture and actionable development plans. Lead engineering teams through development, code review, testing, deployment and production support. Establish and maintain engineering standards covering architecture, coding practices, security, performance and scalability. Evaluate technologies and architectural approaches and make informed technical decisions. Identify technical risks and proactively resolve complex engineering and delivery challenges. Ensure applications meet required standards for security, scalability, reliability, performance and maintainability . Support CI/CD pipelines, cloud deployment, release management and production operations. Participate in technical planning, estimation, architecture reviews and engineering roadmap discussions. Conduct code reviews and provide technical guidance to engineering team members. Mentor developers and promote a culture of ownership, collaboration and continuous improvement. Communicate technical decisions and architecture clearly to both technical and non-technical stakeholders. Требования: Required Qualifications & Technical Skills 7+ years of professional software engineering experience , including significant experience in system design or architecture. Strong hands-on experience with Python and enterprise backend development. Strong experience with FastAPI, Django or equivalent Python frameworks . Proven experience designing and developing RESTful APIs . Strong understanding of microservices and distributed-system architecture . Strong knowledge of database design, data modelling and performance optimization. Strong understanding of application security, authentication and authorization. Proven experience designing large-scale, multi-system architectures . Experience making technical decisions across multiple teams, products or platforms. Strong understanding of software engineering principles, design patterns and development best practices. Cloud & DevOps Hands-on experience with one or more of the following cloud platforms: Amazon Web Services (AWS) Microsoft Azure Google Cloud Platform (GCP) Experience with the following will be an advantage: Docker and containerization CI/CD pipelines Cloud-native application development Infrastructure automation Monitoring and observability Deployment automation AI, Data & Emerging Technologies Experience in one or more of the following will be highly valued: Artificial Intelligence / Machine Learning Generative AI and LLM-based applications Retrieval-Augmented Generation (RAG) Vector databases Agentic AI / AI Agents Data engineering and data platforms Analytics pipelines ML model integration and deployment

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