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 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.
As 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 include:
- Innovative 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
- 7–12+ years total experience in software engineering data engineering machine learning or cloud architecture
- Hands-on experience is expected 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 Experience
- Experience with 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 Experience; 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
- Security Governance and Responsible AI Experience
- AI governance frameworks
- Privacy-by-design
- Model risk management