Lead Cloud Native Developer (Python & AI)

Description

We are looking for a Lead Cloud Native Developer passionate about building scalable, resilient, and observable cloud-native applications with AI at the core. The ideal candidate combines deep Python expertise with cloud engineering experience, technical leadership, and the ability to design and deliver AI-powered solutions. Responsibilities Lead the design, implementation, and deployment of cloud-native solutions using Python, with a focus on scalability, security, performance, and containerization or serverless architectures Design architecture and structure of managed database solutions for efficient data handling Implement observability through monitoring and logging Apply Infrastructure as Code principles to automate cloud infrastructure management and provisioning Drive CI/CD practices for rapid and automated application delivery Design and build AI-integrated solutions, including LLM-based applications, RAG pipelines, and AI agents Mentor team members and conduct code reviews to maintain engineering standards Requirements 5+ years of hands-on experience in software development with a strong emphasis on Python At least 1 year of relevant technical leadership experience Proven experience designing scalable and robust web architecture with an understanding of cost-effectiveness Strong knowledge of cloud-native principles and hands-on experience with cloud services, including containerization and serverless computing Deep Experience with cloud platform (Azure, AWS, or GCP) Hands-on experience implementing application monitoring and logging Practical AI knowledge across two dimensions: leveraging AI-powered development tools (GitHub Copilot, Cursor, or similar) to accelerate delivery, and experience building AI-integrated solutions (LLM APIs, RAG pipelines, AI agents, or integrations with OpenAI / Azure OpenAI) English proficiency at B2 level or higher Nice to have Cloud platform certifications (Azure, AWS, or GCP) Experience with AI/LLM frameworks and tooling: LangChain, LangGraph, LlamaIndex, vector stores (Azure AI Search, pgvector, Pinecone) Familiarity with AI orchestration patterns: multi-agent systems, evaluator-optimizer loops, retrieval-augmented generation Knowledge of advanced cloud-native architectures

Requirements

• 5+ years of hands-on experience in software development with a strong emphasis on Python

• At least 1 year of relevant technical leadership experience

• Proven experience designing scalable and robust web architecture with an understanding of cost-effectiveness

• Strong knowledge of cloud-native principles and hands-on experience with cloud services, including containerization and serverless computing

• Deep Experience with cloud platform (Azure, AWS, or GCP)

• Hands-on experience implementing application monitoring and logging

• Practical AI knowledge across two dimensions: leveraging AI-powered development tools (GitHub Copilot, Cursor, or similar) to accelerate delivery, and experience building AI-integrated solutions (LLM APIs, RAG pipelines, AI agents, or integrations with OpenAI / Azure OpenAI)

• English proficiency at B2 level or higher

Responsibilities

• Lead the design, implementation, and deployment of cloud-native solutions using Python, with a focus on scalability, security, performance, and containerization or serverless architectures

• Design architecture and structure of managed database solutions for efficient data handling

• Implement observability through monitoring and logging

• Apply Infrastructure as Code principles to automate cloud infrastructure management and provisioning

• Drive CI/CD practices for rapid and automated application delivery

• Design and build AI-integrated solutions, including LLM-based applications, RAG pipelines, and AI agents

• Mentor team members and conduct code reviews to maintain engineering standards

Seniority

• Lead

Nice to have

• Cloud platform certifications (Azure, AWS, or GCP)

• Experience with AI/LLM frameworks and tooling: LangChain, LangGraph, LlamaIndex, vector stores (Azure AI Search, pgvector, Pinecone)

• Familiarity with AI orchestration patterns: multi-agent systems, evaluator-optimizer loops, retrieval-augmented generation

• Knowledge of advanced cloud-native architectures