Senior Managing Consultant - AI Architect

About the role

A 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 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.

Leaders are expected to spend time with their teams and clients and therefore are generally expected to be in the workplace a minimum of three days a week subject to business needs.

Responsibilities

• Serve as a leader in defining solutions for clients, advocating for the client while guiding the technical team to implementation.
• Collaborate with client stakeholders and internal partners to understand business problems, requirements, system constraints, and stakeholder concerns to systematically transform detailed solutions (architectures) for the client.
• Innovative Systems Design for Optimal Performance: Design centralized or distributed systems that address user requirements and perform efficiently.
• End-to-End Data Architecture Leadership: Manage end-to-end data architecture, including platform selection, technical architecture design, and application development.
• Data Analysis and Insightful Reporting: Interpret data, analyze results using statistical techniques, and provide ongoing reports to uncover key insights.

Requirements

• 10–12+ years total experience in software engineering, data engineering, machine learning, or cloud architecture.
• Hands-on experience in:
  • Building 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, including:
    • LLM fine-tuning, RAG pipelines, vector databases.
    • Familiarity with OpenAI, Anthropic, Llama, Hugging Face.
    • Prompt engineering, model evaluation, guardrails & safety.
  • Deep experience in at least one cloud platform.
  • Architecture & system design; high-level solution architecture diagrams.
• Experience in Data Engineering & Data Architecture:
  • Data pipelines: Spark, Airflow, Kafka.
  • Data lakes & warehouses: Snowflake, BigQuery, Redshift.
  • ETL/ELT design.
  • Data governance & quality frameworks.
• Experience in Security, Governance, and Responsible AI:
  • AI governance frameworks.
  • Privacy-by-design.
  • Model risk management.

Qualifications

Preferred Education: Master's Degree