Application Architect-AI Integration

IBM India Pvt. Limited; Bengaluru; On-site; INR 3,000,000 - 4,200,000; Full time

Job summary

IBM India Pvt. Limited in Bengaluru seeks an Application Architect for AI Integration to design and govern end-to-end architectures that embed AI capabilities into enterprise applications and workflows.

You will translate business objectives into scalable designs, balance vendor services with custom development, and drive governance for AI integration across prompts, guardrails, and lifecycle management, from design through operations.

Qualifications

• Deep expertise in designing and governing end-to-end architectures embedding AI into enterprise applications and workflows.
• Architecture design: defining reference patterns for AI services, models and orchestration layers including RAG, event-driven and microservices.
• AI governance: governance for prompts, guardrails, lifecycle management with observability, privacy and responsible AI from design to operations.

Responsibilities

• Design architectures for AI services, models and orchestration layers to integrate with APIs and data platforms.
• Collaborate with stakeholders to translate business objectives into scalable, resilient, and policy-compliant designs, balancing vendor-managed services with custom development.
• Govern AI integration by driving governance for prompts, guardrails, and lifecycle management across design and operations.

Skills

Deep AI Expertise

Architecture Design

AI Governance

Technical Leadership

Integration Expertise

Education

Bachelor's Degree

Master's Degree

Job description

Your Role and Responsibilities:

As an Application Architect for AI Integration, this role is responsible for designing and governing end-to-end architectures that embed AI capabilities into enterprise applications and workflows. The Application Architect collaborates with stakeholders to translate business objectives into scalable designs, balancing vendor-managed services with custom development, and drives governance for AI integration.

Your Primary Responsibilities Will Include:

• Designing Architectures: defining reference patterns for AI services, models, and orchestration layers to integrate seamlessly with existing systems, APIs, and data platforms.
• Collaborating with Stakeholders: translating business objectives into scalable, resilient, and policy-compliant designs, ensuring performance, security, compliance, and cost objectives are met.
• Governing AI Integration: driving governance for prompts, guardrails, and lifecycle management, ensuring observability, privacy, and responsible AI principles are embedded from design through operations.

Required Education:

Bachelor's Degree

Preferred Education:

Master's Degree

Required Technical and Professional Expertise:

• Deep AI Expertise: Experience with designing and governing end-to-end architectures that embed AI capabilities into enterprise applications and workflows, ensuring seamless integration with existing systems, APIs, and data platforms.
• Architecture Design: Experience defining reference patterns for AI services, models, and orchestration layers, including Retrieval-Augmented Generation (RAG), event-driven and microservices architectures, and hybrid reasoning.
• AI Governance: Experience driving governance for prompts, guardrails, and lifecycle management, ensuring observability, privacy, and responsible AI principles are embedded from design through operations.
• Technical Leadership: Experience collaborating with stakeholders to translate business objectives into scalable, resilient, and policy-compliant designs, balancing vendor-managed services with custom development.
• Integration Expertise: Experience integrating AI services, models, and orchestration layers with existing systems, APIs, and data platforms, meeting performance, security, compliance, and cost objectives.

Preferred Technical and Professional Experience:

• Advanced AI Knowledge: Deep expertise in AI services, models, and orchestration layers, including Retrieval-Augmented Generation (RAG) and hybrid reasoning.
• Technical Architecture: Experience with event-driven and microservices architectures, ensuring seamless integration with existing systems, APIs, and data platforms.
• AI Governance Tools: Familiarity with tools for driving governance, prompts, guardrails, and lifecycle management, ensuring observability, privacy, and responsible AI principles.

Years of Experience:

22 - 25