AI Architect

Introduction

The AI Architect will play a critical role in driving our clients’ AI transformation journeys and shaping their future digital capabilities. If you are passionate about AI innovation, enjoy complex problem-solving, and thrive in collaborative environments, we invite you to apply.

Your Role And Responsibilities

We are seeking a highly skilled AI Architect to join IBM Consulting’s AI & Analytics practice. In this role, you will help design, implement, and scale AI solutions for clients across multiple industries. The ideal candidate will define AI architectures and solution strategies that align with business objectives, while leveraging the latest advancements in AI, including generative AI, agentic AI systems, and cloud-native AI services.

Required Technical And Professional Expertise

• AI Project Leadership: Minimum 3 years of experience leading AI projects and defining architectural approaches.
• Application Development: 5+ years of experience developing AI-enabled applications using backend frameworks.
• Rapid Prototyping: Demonstrated ability to rapidly develop prototypes and solution blueprints.
• AI Solution Design: Design scalable and efficient AI and generative AI solutions aligned to client business needs.
• Agentic AI Architecture: Experience designing and implementing agentic and autonomous AI systems, including planning, orchestration, tool-use, and multi-agent workflows.
• System Architecture: Architect end-to-end AI systems covering data ingestion, model development, deployment, monitoring, and integration with enterprise environments.
• Cloud AI Services: Design AI solutions using major cloud providers (AWS, Azure, Google Cloud, IBM Cloud), including managed AI/ML and LLM services.
• Cloud Architecture: Develop cloud-native architectures ensuring reliability, security, scalability, and cost optimization for AI workloads.
• Microservices: Design microservices-based architectures to support modular, maintainable, and scalable AI applications.
• API Design: Develop APIs and interfaces for AI services to enable seamless integration with enterprise systems.
• Data Architecture: Design data pipelines, vector databases, feature stores, and data lakes to support AI workloads.
• Security Architecture: Ensure AI systems comply with security and regulatory requirements, including encryption, access control, data governance, and model-level safeguards.
• Machine Learning & AI: Demonstrate proficiency with modern AI/ML techniques, including generative AI models, transformers, embeddings, and NLP.
• Prompt Engineering: Develop and optimize prompts and structured instructions for LLM-based solutions.
• Programming: Proficiency in programming languages such as Python or Java, and frameworks such as Flask, Django, or similar.
• DevOps/MLOps: Familiarity with CI/CD pipelines, automation, and operationalization of AI systems.

Preferred Technical And Professional Experience

• Problem-Solving: Strong analytical abilities and comfort addressing complex technical challenges.
• Communication: Ability to clearly explain technical concepts to both technical and non-technical stakeholders.
• Collaboration: Experience working effectively with cross-functional teams including engineers, data scientists, and business stakeholders.
• Project Management: Ability to manage timelines, deliverables, and stakeholder expectations.
• Cloud and AI Certifications: Certifications from AWS, Azure, Google Cloud, IBM, or equivalent credentials in AI/ML or cloud architecture.

Key skills/competency

• AI Architecture
• Generative AI
• Cloud Computing
• Machine Learning
• Data Pipelines
• Microservices
• API Design
• MLOps
• Prompt Engineering
• Security Architecture