Application Architect-AI Integration

Introduction

A career in IBM Consulting is founded on enduring client partnerships and collaborative efforts across the globe. You will engage with prominent companies from diverse sectors, assisting them in navigating their hybrid cloud and AI transformations. With the backing of our strategic partners, advanced IBM technology, and Red Hat, you will be equipped to instigate significant change and enhance client outcomes. At IBM Consulting, a spirit of curiosity drives our achievements. You will be empowered to question the status quo, investigate innovative ideas, and develop creative solutions that yield tangible results. Our environment fosters growth and empathy, prioritizing your long-term career advancement while appreciating your distinct skills and experiences.

Your Role And Responsibilities

In the capacity of an Application Architect specializing in AI Integration, you will be tasked with designing and overseeing comprehensive architectures that incorporate AI functionalities into enterprise applications and workflows. The Application Architect engages with stakeholders to convert business goals into scalable designs, balancing vendor-managed services with custom development, while ensuring robust governance for AI integration.

Your Primary Responsibilities Will Include

• Designing Architectures: Establishing reference patterns for AI services, models, and orchestration layers to ensure seamless integration with current systems, APIs, and data platforms.
• Collaborating with Stakeholders: Converting business objectives into scalable, resilient, and policy-compliant designs, while guaranteeing that performance, security, compliance, and cost targets are achieved.
• Governing AI Integration: Leading governance initiatives for prompts, guardrails, and lifecycle management, ensuring that observability, privacy, and responsible AI principles are woven into the design and operational phases.
  
  

Preferred Education

Master's Degree

Required Technical And Professional Expertise

• AI Architecture Design: Proficiency in designing comprehensive architectures that integrate AI capabilities into enterprise applications and workflows, ensuring smooth integration with existing systems, APIs, and data platforms.
• Technical Governance: Proven experience in establishing governance protocols for prompts, guardrails, and lifecycle management, ensuring observability, privacy, and adherence to responsible AI principles throughout the design and operational processes.
• Reference Pattern Development: Expertise in creating reference patterns for AI services, models, and orchestration layers, including Retrieval-Augmented Generation (RAG) and hybrid reasoning methodologies.
• Stakeholder Collaboration: Skilled in working with stakeholders to transform business goals into scalable, resilient, and policy-compliant designs, effectively balancing vendor-managed services and custom development.
• AI Service Integration: Demonstrated experience in integrating AI services, models, and orchestration layers with existing systems, APIs, and data platforms, achieving performance, security, compliance, and cost-related objectives.
  
  

Preferred Technical And Professional Experience

• Advanced AI Concepts: Familiarity with emerging AI technologies and trends, such as explainable AI and edge AI, is a plus.
• Cloud Native Services: Knowledge of cloud-native services and serverless architectures is advantageous for designing scalable AI integrations.
• Data Platform Integration: Experience with integrating AI services across various data platforms and APIs is beneficial.