AI Architect - Managing Consultant

IntroductionA career in IBM Consulting is built on long-term client relationships and close collaboration worldwide. You’ll work with leading companies across industries, helping them shape their hybrid cloud and AI journeys. With support from our strategic partners, robust IBM technology, and Red Hat, you’ll have the tools to drive meaningful change and accelerate client impact. At IBM Consulting, curiosity fuels success. You’ll be encouraged to challenge the norm, explore new ideas, and create innovative solutions that deliver real results. Our culture of growth and empathy focuses on your long-term career development while valuing your unique skills and experiences.Your Role And ResponsibilitiesAs an Architect in IBM Consulting, you'll serve as a leader in defining solutions for clients. You'll be the advocate for the client while guiding the technical team to implementation.You'll collaborate with client stakeholders and internal partners to understand the business problem and requirements, constraints of the system and concerns of the various stakeholders to systematically transform detailed solutions (architectures) for the client.Your Primary Responsibilities IncludeInnovative Systems Design for Optimal Performance: Design centralized or distributed systems that both address the user's requirements and perform efficiently and effectively.End-to-End Data Architecture Leadership: Manage end-to-end data architecture, starting from selecting the platform, designing a technical architecture and developing the application.Data Analysis and Insightful Reporting: Interpret data, analyze results using statistical techniques and provide ongoing reports discovering key insights.Required Technical And Professional Expertise7–12+ years total experience in software engineering, data engineering, machine learning, or cloud architecture.Deep experience in at least one cloud platform.Architecture & System Design Experience; high-level solution architecture diagrams.Hands-on Experience Is Expected InBuilding and deploying ML models (supervised, unsupervised, deep learning).Model lifecycle & MLOps: MLflow, Kubeflow, Vertex AI, SageMaker.Feature engineering and dataset management.Large Language Models & Generative AI ExperienceExperience with LLM fine-tuning, RAG pipelines, vector databases.Familiarity with OpenAI, Anthropic, Llama, Hugging Face.Prompt engineering, model evaluation, guardrails & safety.Preferred Technical And Professional ExperienceExperience in Data Engineering & Data ArchitectureData pipelines: Spark, Airflow, Kafka.Data lakes & warehouses: Snowflake, BigQuery, Redshift.ETL/ELT design.Data governance & quality frameworks.Security, Governance, And Responsible AI ExperienceAI governance frameworks.Privacy-by-design.Model risk management.