Role Purpose Lead the design, development, and delivery of advanced Natural Language Understanding (NLU) solutions leveraging Large Language Models (LLMs) for text and reasoning tasks. Ensure technical excellence, innovation, and alignment with Omilia’s strategic objectives in conversational AI. Accountabilities - Technical Correctness: Own the technical integrity and quality of NLU solutions, ensuring robust, scalable, and maintainable code and models. - System Quality: Oversee architectural decisions, code reviews, and best practices for LLM-based NLU systems. - Delivery Monitoring: Ensure timely and successful delivery of NLU features and improvements, proactively identifying and mitigating risks. - Autonomy: Operate with high independence, making critical technical decisions and setting standards for the team. - Scope & Complexity: Lead initiatives involving complex reasoning, multi-turn dialogue, and advanced text understanding, often spanning multiple projects or products. - Impact: Drive measurable improvements in NLU accuracy, performance, and customer satisfaction. - Influence/Mentorship: Mentor engineers and data scientists, fostering a culture of technical excellence and continuous learning. Key Responsibilities - Design and implement state-of-the-art LLM-based NLU models for text and reasoning tasks. - Lead technical discussions, architecture reviews, and solution design sessions. - Collaborate with cross-functional teams (Product, Data Science, Engineering) to define requirements and deliver solutions. - Conduct code and model reviews, ensuring adherence to best practices and Omilia standards. - Monitor system performance, troubleshoot issues, and drive continuous improvement. - Stay abreast of advancements in LLMs, NLU, and AI, evaluating and integrating relevant technologies. - Provide technical mentorship and guidance to team members.

Role Purpose Lead the design, development, and delivery of advanced Natural Language Understanding (NLU) solutions leveraging Large Language Models (LLMs) for text and reasoning tasks. Ensure technical excellence, innovation, and alignment with Omilia’s strategic objectives in conversational AI. Accountabilities - Technical Correctness: Own the technical integrity and quality of NLU solutions, ensuring robust, scalable, and maintainable code and models. - System Quality: Oversee architectural decisions, code reviews, and best practices for LLM-based NLU systems. - Delivery Monitoring: Ensure timely and successful delivery of NLU features and improvements, proactively identifying and mitigating risks. - Autonomy: Operate with high independence, making critical technical decisions and setting standards for the team. - Scope & Complexity: Lead initiatives involving complex reasoning, multi-turn dialogue, and advanced text understanding, often spanning multiple projects or products. - Impact: Drive measurable improvements in NLU accuracy, performance, and customer satisfaction. - Influence/Mentorship: Mentor engineers and data scientists, fostering a culture of technical excellence and continuous learning. Key Responsibilities - Design and implement state-of-the-art LLM-based NLU models for text and reasoning tasks. - Lead technical discussions, architecture reviews, and solution design sessions. - Collaborate with cross-functional teams (Product, Data Science, Engineering) to define requirements and deliver solutions. - Conduct code and model reviews, ensuring adherence to best practices and Omilia standards. - Monitor system performance, troubleshoot issues, and drive continuous improvement. - Stay abreast of advancements in LLMs, NLU, and AI, evaluating and integrating relevant technologies. - Provide technical mentorship and guidance to team members.

Role Purpose Lead the design, development, and delivery of advanced Natural Language Understanding (NLU) solutions leveraging Large Language Models (LLMs) for text and reasoning tasks. Ensure technical excellence, innovation, and alignment with Omilia’s strategic objectives in conversational AI. Accountabilities - Technical Correctness: Own the technical integrity and quality of NLU solutions, ensuring robust, scalable, and maintainable code and models. - System Quality: Oversee architectural decisions, code reviews, and best practices for LLM-based NLU systems. - Delivery Monitoring: Ensure timely and successful delivery of NLU features and improvements, proactively identifying and mitigating risks. - Autonomy: Operate with high independence, making critical technical decisions and setting standards for the team. - Scope & Complexity: Lead initiatives involving complex reasoning, multi-turn dialogue, and advanced text understanding, often spanning multiple projects or products. - Impact: Drive measurable improvements in NLU accuracy, performance, and customer satisfaction. - Influence/Mentorship: Mentor engineers and data scientists, fostering a culture of technical excellence and continuous learning. Key Responsibilities - Design and implement state-of-the-art LLM-based NLU models for text and reasoning tasks. - Lead technical discussions, architecture reviews, and solution design sessions. - Collaborate with cross-functional teams (Product, Data Science, Engineering) to define requirements and deliver solutions. - Conduct code and model reviews, ensuring adherence to best practices and Omilia standards. - Monitor system performance, troubleshoot issues, and drive continuous improvement. - Stay abreast of advancements in LLMs, NLU, and AI, evaluating and integrating relevant technologies. - Provide technical mentorship and guidance to team members.

Role Purpose To lead the technical development and continuous improvement of Omilia’s proprietary LLM and NLU service portfolio, powering the reasoning and language understanding layer of the enterprise-grade Self-Learning Agentic CX Platform. This role ensures technical correctness, system quality, and delivery monitoring for mission-critical AI services that enable autonomous agents to reason, plan, execute tasks, and self-improve in real customer conversations. Accountabilities - Technical Ownership: Hold final technical authority over all LLM/NLU services, including entity/intent classification, specialized LLMs, and agentic orchestration. - System Quality: Ensure production stability, performance, and compliance (including PCI/PII) across the LLM/NLU domain. - Delivery Monitoring: Commit to delivery dates, drive features from design through deployment, and proactively flag risks. - Autonomy: Resolve technical ambiguity, structure loosely defined requirements, and make architectural decisions independently. - Scope & Complexity: Lead the most complex, ambiguous, or cross-cutting features, including model research, agentic reasoning, and inference server development. - Impact: Directly influence the quality and reliability of AI services serving millions of customer interactions in regulated industries. - Influence/Mentorship: Guide and mentor mid-level and junior engineers through code reviews, pairing, and knowledge transfer; drive alignment between Product, Architecture, and Engineering. Key Responsibilities - Lead research and experimentation on new model architectures, training strategies, and evaluation methodologies for LLM/NLU. - Design, develop, fine-tune, and evaluate specialized LLMs for Concierge and Task Agents. - Develop and optimize ML pipelines for training, evaluation, and deployment (AWS SageMaker). - Architect and maintain inference servers, ensuring low latency and high reliability. - Implement and evolve closed-loop self-learning systems for continuous model improvement. - Drive benchmarking, experiment reproducibility, and documentation quality. - Ensure compliance with data privacy standards throughout the ML lifecycle. - Mentor and support the growth of team members; share expertise via tech talks and guides.