Lead AI Consultant

The Work You’ll Do

• Advise and Safeguard Technical Implementations: Provide architectural oversight for concurrent deployments at Fortune 500 organizations. Act as the final technical authority, maintaining "project-ready" coding skills to troubleshoot and resolve critical production failures that block value realization.
• Architect AI-Enriched Solutions: Collaborate with pre-sales teams to transform experimental prototypes into robust, scalable enterprise applications. Translate successful deployments into standardized platform features by maintaining a tight feedback loop with Product and Engineering.
• Engineer Low-Latency Systems: Optimize AI-enriched solutions for high-throughput and minimal latency. Ensure the Celonis Platform handles near-real-time data integration without compromising the user experience of business-critical applications.
• Implement Eval-Ops & Automated Testing: Build rigorous evaluation pipelines to test LLM quality and reliability at scale. Move beyond manual spot-checks by institutionalizing automated benchmarks for model accuracy and safety.
• Deploy LLMOps & Lifecycle Governance: Design systems for continuous model monitoring, cost optimization, and performance tuning. Establish frameworks for data privacy and compliance within the customer's actual IT environment.
• Troubleshoot Agentic Orchestration: Manage the complexity of multi-agent workflows where agentic activity is triggered by Celonis context and logged back to the platform. Ensure seamless hand-offs between agents and maintain the integrity of the full process loop.

Preferred Qualifications

• Architectural Leadership: Proven experience designing and scaling innovative AI solutions within actual customer IT environments, moving these solutions from pilot to production.
• Advanced Technical Production: Ability to refactor experimental pilots for production-scale performance and a deep proficiency in Python for building enterprise-grade LLM-based solutions.
• Vertical Industry Expertise: In-depth understanding of complex business challenges within a specific industry vertical (e.g., Manufacturing, Life Sciences).
• Senior Stakeholder Management: Excellence in translating highly complex architectural concepts and AI governance frameworks into strategic roadmaps for C-suite stakeholders.
• Lifecycle Mastery: Experience in production-level acceptance testing, low-latency system design, and the management of ongoing LLM performance.
• Academic Excellence: Bachelor’s degree or higher in Computer Science, Engineering, Mathematics, or a related quantitative field.