Lead Cloud Native Developer (Python & AI)

Job 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