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Strong employer brand, popular AI Engineer title, and broad full-stack AI skill requirements drive high competition.
AI engineering skills transfer across industries but enterprise integration and corporate affairs context increase domain specificity.
Explicit 8-12 year requirement, mandatory production ML/LLM experience and enterprise integration skills.
Build, deploy, and optimize AI applications and workflows addressing corporate affairs use cases, ensuring practical adoption at scale.
Own front-end user interface development to deliver reliable, usable AI tools aligned with business priorities.
Monitor and maintain production AI solutions, focusing on sustained performance, user experience, and measurable business impact.
Bachelor’s degree in Computer Science, AI, Machine Learning, Data Science, Engineering, or related technical field or equivalent experience.
8-12 years of relevant experience with at least 3 years deploying production-grade AI or generative AI solutions in corporate settings.
Strong experience with AI platforms (Claude, GPT, Azure OpenAI, Langfuse, vector DBs), large language models, prompt engineering, workflow orchestration, and production support.
Experience integrating AI with enterprise data sources, cloud platforms, APIs, and ensuring solution reliability and compliance.
Experienced in transitioning AI projects from prototype to production while maintaining engineering discipline and scalability.
Proven ability to deliver measurable business outcomes using AI solutions in a corporate environment.
Skilled at collaborating across functions (product owners, data teams, IT) in agile or delivery-driven contexts to align AI solutions with business needs.