Your Role
Defines Agentic AI solution architecture, platform patterns, integration strategy, governance, security controls, and scalable multi-agent design. Ensures alignment with enterprise standards and production readiness.
What you will do:
1. AI Strategy & Architecture
Define enterprise Agentic AI architecture and technology roadmap.
Design scalable, modular, and reusable AI agent frameworks.
Establish architectural standards, governance, and best practices for AI solutions. Evaluate emerging AI technologies and recommend adoption strategies. Drive AI modernization initiatives across business units.
2. Agentic AI Solution Design
Design autonomous AI agents capable of planning, reasoning, memory management, tool usage, and task execution.
Architect multi-agent collaboration patterns for complex workflows.
Design orchestration mechanisms for agent communication and coordination.
Define agent lifecycle management including planning, execution, reflection, and optimization.
Build reusable AI capabilities across multiple enterprise use cases.
3. LLM & GenAI Architecture
Architect solutions leveraging foundation models such as GPT, Claude, Gemini, Llama, Mistral, and enterprise-hosted models.
Design Retrieval-Augmented Generation (RAG) architectures.
Develop prompt engineering and prompt management strategies.
Design semantic search using vector databases.
Optimize AI inference performance, latency, and operational costs.
4. AI Platform & Engineering
Architect scalable AI platforms on Azure, AWS, or Google Cloud.
Design APIs and microservices supporting AI workloads.
Integrate AI agents with enterprise systems such as SAP, ServiceNow, Salesforce, Microsoft 365, Jira, Slack, and internal applications.
Build reusable AI accelerators and reference architectures.
Define CI/CD pipelines for AI applications (LLMOps/MLOps).
5. Data & Knowledge Architecture
Design enterprise knowledge ingestion pipelines.
Architect document processing, embeddings, vector indexing, and metadata management.
Define strategies for structured and unstructured data integration.
Design knowledge graphs and semantic retrieval architectures where appropriate.
6. Governance, Security & Responsible AI
Establish Responsible AI guidelines and governance.
Ensure compliance with enterprise security policies and regulatory standards.
Implement guardrails against hallucinations, prompt injection, and data leakage.
Design authentication, authorization, audit logging, and AI monitoring frameworks.
Ensure explainability, transparency, and ethical AI practices.
7. Leadership & Collaboration
Lead architecture reviews and technical design sessions.
Mentor architects, AI engineers, and development teams.
Partner with business leaders to identify AI transformation opportunities.
Drive proof-of-concepts through production deployment.
Your Future at Kyndryl
Every position at Kyndryl offers a way forward to grow your career. We have opportunities that you won’t find anywhere else, including hands-on experience, learning opportunities, and the chance to certify in all four major platforms. Whether you want to broaden your knowledge base or narrow your scope and specialize in a specific sector, you can find your opportunity here.
