Lead AI Engineer | Join with Sign-on Bonus

We are seeking aLead AI Engineer to spearhead the design and architecture of enterprise-grade AI agentic solutions. In this role, you will drive innovation across LLMs, foundation models, and multi-agent systems while shaping production AI platforms and fostering a high-performance engineering culture. You will collaborate with cross-functional teams to deliver measurable business impact through cutting-edge AI technologies.

Please read the Terms & Conditionshere.

Responsibilities

• Lead, design and architect enterprise-grade AI agentic solutions using LLMs, foundation models and multi-agent systems
• Implement production AI platforms with modular pipelines, multi-source knowledge fusion and governance frameworks
• Collaboration with product, engineering and business teams to understand requirements and drive strategic decisions
• Architecture of hybrid AI systems combining agentic AI, traditional ML, symbolic reasoning and knowledge graphs
• Perform detailed analysis of business problems and design comprehensive solutions with measurable ROI
• Establish MLOps/AIOps practices including continuous evaluation, A/B testing, model versioning and automated retraining pipelines
• Lead code and architecture reviews, ensuring solutions meet security, compliance and best practice standards
• Foster a high-performance AI engineering culture, mentor team members and provide technical leadership
• Design evaluation frameworks covering technical, human-centered, temporal and contextual metrics
• Drive innovation and stay current with emerging AI technologies and research
• Author comprehensive technical documentation, architecture decision records and knowledge base articles

Requirements

• 5+ years of experience in AI/ML engineering with proven leadership in architecting enterprise-grade solutions
• Expertise in LLMs, foundation models and multi-agent systems
• Proficiency in designing production AI platforms with modular pipelines and governance frameworks
• Background in hybrid AI systems combining agentic AI, traditional ML and symbolic reasoning
• Knowledge of knowledge graphs and multi-source knowledge fusion
• Competency in MLOps/AIOps practices including A/B testing, model versioning and automated retraining
• Capability to design evaluation frameworks covering technical, human-centered and contextual metrics
• Understanding of business problem analysis and translating requirements into solutions with measurable ROI
• Showcase of strong cross-functional collaboration and stakeholder management
• Familiarity with security, compliance standards and emerging AI research trends
• English proficiency at B2 level or higher