Agentic AI Architect at Kyndryl Canada Limited

Hyderabad, Telangana, India -

Full Time

Start Date

Immediate

Expiry Date

11 Oct, 26

Salary

0.0

Posted On

13 Jul, 26

Experience

10 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Agentic AI, Large Language Models, Multi-Agent Systems, RAG, Prompt Engineering, LangChain, LangGraph, Azure OpenAI, AWS Bedrock, Google Vertex AI, Python, Vector Databases, LLMOps, Cloud Architecture, Enterprise Integration, Responsible AI

Industry

IT Services and IT Consulting

Description

Who We Are At Kyndryl, we run and reimagine the mission-critical technology systems that drive advantage for the world’s leading businesses. We are at the heart of progress; with proven expertise and a continuous flow of AI-powered insight, enabling smarter decisions, faster innovation, and a lasting competitive edge. For our people—Kyndryls—that means doing purposeful work that powers human progress. Join us and experience a flexible, supportive environment where your well-being is prioritized and your potential can thrive. The Role 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. 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. 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. 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. 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). 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. 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. 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. Required Technical Skills Artificial Intelligence Large Language Models (LLMs) Agentic AI Multi-Agent Systems Autonomous AI Agents Retrieval-Augmented Generation (RAG) Prompt Engineering AI Reasoning & Planning AI Memory Architectures AI Evaluation Frameworks Frameworks LangChain LangGraph Microsoft AutoGen CrewAI LlamaIndex OpenAI SDK Cloud Platforms Microsoft Azure Azure OpenAI Service AWS Bedrock Google Vertex AI Kubernetes Docker Programming Python Java C# JavaScript/TypeScript REST APIs FastAPI .NET Data Technologies SQL NoSQL Vector Databases (Pinecone, Milvus, Weaviate, Azure AI Search, ChromaDB) Elasticsearch Cosmos DB DevOps & AI Operations GitHub Azure DevOps Jenkins Terraform CI/CD MLflow LangSmith Azure AI Foundry PromptFlow AI Monitoring and Observability 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. Who You Are You’re good at what you do and possess the required experience to prove it. However, equally as important – you have a growth mindset; keen to drive your own personal and professional development. You are customer-focused – someone who prioritizes customer success in their work. And finally, you’re open and borderless – naturally inclusive in how you work with others. Experience 12–18+ years in Software Engineering, AI/ML, Cloud Architecture, or Enterprise Solution Architecture, with at least 3–5 years designing and implementing Generative AI solutions. Required Qualifications Bachelor's degree in Computer Science, Engineering, Information Technology, or related field. 12–18+ years of software engineering or architecture experience. 5+ years in AI/ML or Generative AI architecture. Experience delivering enterprise-scale AI solutions. Strong understanding of cloud-native architectures. Experience with enterprise integration patterns. Excellent communication, stakeholder management, and leadership skills. Preferred Certifications (not mandatory) Microsoft Certified: Azure AI Engineer Associate Microsoft Certified: Azure Solutions Architect Expert Microsoft Certified: Azure OpenAI Service (if applicable) AWS Certified Machine Learning – Specialty Google Professional Machine Learning Engineer TOGAF Kubernetes Certification (CKA/CKAD) Success Metrics Successful deployment of production-grade Agentic AI solutions. Reduction in manual effort through autonomous AI workflows. Improved business productivity and operational efficiency. High AI reliability, security, and governance compliance. Reusable enterprise AI architecture and accelerators. Positive stakeholder adoption and measurable business outcomes. Being You The “Kyn” in Kyndryl means kinship, which represents the strong bonds we have with each other, our customers and our communities. We focus on ensuring all Kyndryls feel included and we welcome people of all cultures, backgrounds, and experiences. Even if you don’t meet every requirement, we encourage you to apply. We believe in growth, and we’re excited to see what you can bring. At Kyndryl, employee feedback has told us that our number one driver of employee engagement is belonging. That sense of belonging — being a valued, respected, trusted member of the team — is fundamental to our culture and fueling great experiences for our customers. This dedication to welcoming everyone into our company means that Kyndryl gives you the ability to thrive and contribute to our culture of empathy and shared success. That’s The Kyndryl Way. What You Can Expect Your career with us isn’t just a job—it’s an adventure with purpose. We offer a dynamic, hybrid-friendly culture that supports your well-being and empowers you to grow. Our Be Well programs are thoughtfully designed to support your financial, mental, physical, and social health—because we know that when you feel your best, you do your best. From your very first day, you’ll dive into impactful work that powers the systems our customers rely on every day. You won’t just contribute—you’ll make a difference, tackling meaningful projects that sharpen your skills and fuel your growth. We’re here to champion your journey. With powerful tools to chart your career path, personalized development goals aligned with your ambitions, and continuous feedback to keep you inspired and on track, you’ll have everything you need to thrive and evolve. You’ll develop in-demand skills to grow your career and achieve your ambitions with access to cutting-edge learning opportunities—from certifications with Microsoft, Google, and Amazon to coaching and hands-on experiences. And through it all, you’ll be part of a culture that values empathy, restless learning, and a devotion to shared success. We want you to thrive here—and we’re committed to helping you do just that. Ready to make an impact? Join us and help shape what’s next. Get Referred! If you know someone that works at Kyndryl, when asked ‘How Did You Hear About Us’ during the application process, select ‘Employee Referral’ and enter your contact's Kyndryl email address. We’re glad you’re here. Take a look around at the many exciting career opportunities we have available and apply today! Can’t find a suitable job opening? Drop off your CV/Resume Drop off your CV/Resume and a Recruiter will reach out with related career information that match your experience and expertise. Sign up for Job Alerts Create your account and then sign up for job alerts. When new jobs become available that meet your criteria, you’ll be alerted right away! At Kyndryl, we achieve progress the world depends on, with purpose. Beginning with the purpose that matters to you. Because here, you will be part of a culture designed with purpose. One that is restless, empathetic and devoted. Where we are committed to sustainable progress for our customers and supporting the communities where we work and live. All of you is what we want. And what we need. Join us, and together, we can advance the vital systems that power human progress.

Responsibilities

Define and design scalable Agentic AI architectures, platform patterns, and multi-agent collaboration frameworks for enterprise use cases. Lead the integration of AI agents with enterprise systems while ensuring governance, security, and production readiness.