Lead AI Developer

Required Experience & Skills

• Approximately Total 10 years of professional software engineering experience.

• Relevant 3+ years of hands-on experience with AI/Generative AI technologies, or equivalent demonstrable

recent experience applying AI extensively in real-world software engineering.

• Strong hands-on experience with modern software development, architecture, testing and engineering

practices.

• Significant recent, hands-on experience using AI extensively in software development.

• Practical experience with AI-powered development tools such as Cursor, Claude, GitHub Copilot or equivalent.

• Ability to demonstrate real projects where AI improved development speed, quality, automation or engineering

outcomes.

• Strong understanding of software architecture, design patterns, APIs, cloud-based systems and modern

development practices.

• Strong problem-solving, analytical and technical communication skills.

• Demonstrated ability to mentor senior and junior engineers and influence teams without formal authority.

• Strong curiosity, experimentation mindset and willingness to continuously learn emerging AI technologies.

Desirable Experience

• Experience with LLMs, Generative AI and AI-assisted software engineering workflows.

• Experience with Anthropic/Claude, OpenAI or other leading LLM ecosystems.

• Experience with prompt engineering, context engineering and AI agent workflows.

• Experience in integrating LLM capabilities into software applications or engineering platforms.

• Experience with locally hosted or open-source LLMs.

• Experience evaluating AI models, agents or AI development frameworks.

• Experience defining AI coding standards, engineering guidelines or governance practices.

• Experience leading AI transformation or AI adoption within a software engineering organization.

What We Are Looking For

• A hands-on practitioner who actively uses AI in software development, rather than someone with only

theoretical AI knowledge.

• A technical leader who can turn AI experimentation into practical, repeatable engineering practices.

• Someone who proactively identifies opportunities and constructively challenges existing ways of working.

• A strong mentor who can influence experienced engineers and develop less-experienced developers.

• A pragmatic engineer who balances innovation with quality, security, maintainability and business value.

• Recent practical AI experience is more important than simply having many years of AI/ML experience.