Expert AI Engineer

About the role

We are seeking an experienced Expert AI Engineer to join an international technology project and help build and scale an internal AI platform used by engineering and non‑technical teams. This hands‑on position focuses on delivering production‑grade AI tools, agents, integrations and automation solutions.

Key responsibilities

• Design, build, deploy and maintain internal AI platforms and AI‑powered tools.
• Develop custom AI skills, Model Context Protocol (MCP) connectors, integrations and agentic workflows.
• Build scalable infrastructure for hosting AI models, integrations and automated execution pipelines.
• Implement multi‑agent orchestration pipelines for complex engineering and business processes.
• Ensure secure AI implementation, including credential management, least‑privilege access, prompt‑injection protection and data‑leakage prevention.
• Integrate AI solutions with existing engineering and business systems and establish governance, security, quality and reliability standards.
• Optimize LLM usage and infrastructure costs through model routing, semantic caching and usage controls.
• Support engineering teams in adopting AI tools and measure impact on productivity and delivery.

Required profile

• 10+ years of professional software development experience with strong backend engineering and system design background.
• Hands‑on experience building and shipping production AI solutions, including AI agents, MCP integrations and custom AI tools.
• Proven ability to lead AI adoption within engineering teams and translate technical concepts into business‑aligned solutions.
• Excellent communication and leadership skills with native‑level English proficiency.

Required skills

• Python, TypeScript/Node.js, Go, Java (or comparable backend language).
• Cloud platforms: AWS, GCP or Azure.
• Docker, Terraform (IaC), CI/CD pipelines.
• Observability tools such as Datadog or ELK.
• Experience with LLM‑based applications, AI agents, and Model Context Protocol integrations.
• Knowledge of AI security practices: credential management, access controls, prompt‑injection mitigation.