Senior Staff AI Architect

Summary

Join ServiceNow's Connected Customer Experience (CCX) team as a Senior Staff AI Architect to build the Connected AI Platform. You will design and implement scalable AI/ML systems enhancing personalization, intent recognition, and conversational capabilities. This role involves architecting intelligent, production-ready AI capabilities across the ServiceNow platform, partnering with ML engineers and data architects, and building reusable AI services and APIs. You will also provide technical insight and strategic guidance, collaborating with various teams to integrate AI into core workflows and customer experiences. The ideal candidate possesses deep expertise in AI/ML systems design, personalization, and experience in digital technology and enterprise software environments. You will ensure ethical AI practices, data privacy, and security are embedded in every solution.

Requirements

• Experience in leveraging or critically thinking about how to integrate AI into work processes, decision-making, or problem-solving. This may include using AI-powered tools, automating workflows, analyzing AI-driven insights, or exploring AI’s potential impact on the function or industry
• 12+ years of experience in AI/ML systems, machine learning architecture, or applied data science, including 3+ years in a senior technical leadership role
• A track record of delivering production-ready ML systems in areas such as search, NLP, personalization, recommendation, or classification
• Expertise in ranking models, embeddings, intent recognition, NLU/NLP, and strategies for personalized user experiences
• Proficiency with machine learning frameworks (e.g., TensorFlow, PyTorch, Hugging Face), orchestration tools (e.g., LangChain), and vector databases (e.g., FAISS, Pinecone, Weaviate)
• Experience with search/retrieval platforms (e.g., Elastic, Vespa, OpenSearch) and conversational systems (e.g., Dialogflow, LLM agents)
• Hands-on experience deploying LLMs, crafting prompts, and building RAG systems in production environments
• Familiarity with MLOps tools such as MLflow, SageMaker, Vertex AI, or Databricks ML
• Strong communication and collaboration skills, with the ability to connect technical ideas to business needs

Responsibilities

• Shape the Future of Intelligent Experiences
• Design and implement scalable AI/ML systems that enhance personalization, intent recognition, semantic search, and conversational capabilities
• Take ownership of architecture across real-time (online) and batch (offline) inference systems that support the platform
• Partner with ML engineers and data architects to ensure effective data pipelines, thoughtful feature design, and seamless model integration
• Build Adaptive, Scalable AI Platforms
• Develop reusable AI services, APIs, and tools that support teams in delivering intelligent, data-driven solutions
• Assess and recommend infrastructure for AI/ML, including feature stores, vector databases, and large language model (LLM) frameworks
• Guide solution development for GenAI applications, such as retrieval-augmented generation (RAG), prompt workflows, and model fine-tuning
• Provide Technical Insight and Strategic Guidance
• Collaborate closely with product, engineering, and platform teams to integrate AI into core workflows and customer experiences
• Support alignment across teams around architectural decisions, balancing scalability, performance, and user-focused design
• Translate emerging AI capabilities into practical, reliable services that teams can build on with clarity and confidence
• Support Responsible and Transparent AI
• Design for visibility—enabling performance tracking, feedback loops, and opportunities for continuous improvement
• Ensure ethical AI practices, data privacy, and security are embedded in every solution and decision

Preferred Qualifications

• Experience working with or building on the ServiceNow platform, especially for intelligent or AI-augmented services
• Understanding of enterprise workflows and systems—particularly in customer service, case management, or operations
• Demonstrated impact in developing personalized or recommendation-based experiences at scale
• Knowledge of event-driven systems, microservices, and API-first development principles
• Comfortable working in cross-functional, matrixed environments—skilled in building connections and influencing outcomes