Application Architect-AI Integration
IBM · Bengaluru · onsite · Posted 40d ago
Undisclosed10–12 yrsfulltimeSourced from
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About this role
Your Role and Responsibilities:
Your primary responsibilities will include:
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:
AI Architecture Design: Experience with designing end-to-end architectures that embed AI capabilities into enterprise applications and workflows, ensuring seamless integration with existing systems, APIs, and data platforms.
Technical Governance: Experience with driving governance for prompts, guardrails, and lifecycle management, ensuring observability, privacy, and responsible AI principles are embedded from design through operations.
Reference Pattern Development: Experience with defining reference patterns for AI services, models, and orchestration layers, including Retrieval-Augmented Generation (RAG) and hybrid reasoning.
Stakeholder Collaboration: Experience with collaborating with stakeholders to translate business objectives into scalable, resilient, and policy-compliant designs, balancing vendor-managed services with custom development.
AI Service Integration: Experience with 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 Concepts: Experience with emerging AI technologies and trends, such as explainable AI and edge AI, can be beneficial.
Cloud Native Services: Knowledge of cloud-native services and serverless architectures can be advantageous in designing scalable AI integrations.
Data Platform Integration: Familiarity with integrating AI services with various data platforms and APIs can be useful.
Years of Experience:
10 - 12
10 - 12
Sourced from naukri
Skills
observabilityRetrieval Augmented Generationai integrationorchestrationapisai servicescloud nativedata platformsai technologiesenterprise applicationsintegrationsEmbedded SystemscloudArchitectureoperationscomplianceArtificial Intelligence
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