GenAI Engineer

Responsibilities

• Design and develop scalable GenAI applications and production-grade APIs using Python, FastAPI, and FastMCP.
• Build and implement agentic workflows and LLM-powered solutions.
• Integrate applications with LLMs such as OpenAI GPT and Anthropic Claude.
• Develop and deploy solutions within Microsoft Azure environments.
• Own end-to-end application development, deployment, monitoring, and observability.
• Implement containerization and CI/CD practices using Docker, Kubernetes/AKS, and GitHub Actions.
• Use AI-assisted development tools such as Claude, Codex, and VS Code to accelerate development, debugging, and delivery.

Skills Must have

• Candidates must have ALL five mandatory skills: FastAPI, FastMCP, Agentic Workflows, LLM/GenAI, and Microsoft Azure along with strong proficiency in Python, with proven experience designing, developing, and implementing applications using FastAPI and FastMCP.
• Candidates should have hands-on experience developing GenAI solutions and integrating LLMs such as OpenAI GPT and Anthropic Claude, as well as experience with deployment, monitoring, observability, containerization, and modern DevOps practices:
• Ability to build scalable, production-grade APIs and end-to-end solutions, covering the complete development lifecycle from implementation and deployment to monitoring and observability.
• Experience with Microsoft Azure is highly preferred.
• Familiarity with Azure services such as AKS, Cosmos DB, and Azure Cache for Redis is a strong plus.
• Solid hands-on experience across the Generative AI ecosystem, including developing applications that consume and integrate with LLMs such as OpenAI GPT and Anthropic Claude.
• Strong hands-on experience with AI-assisted development tools and IDEs, such as Claude, Codex, and VS Code.
• Good understanding of DevOps and containerisation practices, including experience with GitHub Actions, Docker, and Kubernetes / AKS.