Lead Agentic & AI Architect

Who We Are

At Kyndryl, we design, build, manage and modernize the mission-critical technology systems that the world depends on every day. So why work at Kyndryl? We are always moving forward - always pushing ourselves to go further in our efforts to build a more equitable, inclusive world for our employees, our customers and our communities.

The Role

We're looking for exceptional talent to join our AI Agentic Innovation Hub at Kyndryl!

Job Description

As Lead AI Architect at Kyndryl's AI Innovation Hub, you'll be at the core of one of the most ambitious and transformative technological initiatives - designing and guiding the technical architecture behind next-generation AI and Agentic AI global solutions.
You'll shape scalable, secure, and high-performance ecosystems that turn complex business goals into robust, enterprise-grade systems. Acting as both a visionary and a guardian of technical excellence, you'll define the standards that drive reliability, innovation, and responsible AI across the Hub.

This is a leadership role for those who combine architectural mastery with a builder's mindset - who understand that great AI systems are not only powerful, but elegant, traceable, and sustainable. You will have the opportunity to work with the most advanced and powerful technologies, and to collaborate closely with some of the most recognized professionals like data scientists, ML engineers, and business leaders to create architectures that deliver measurable impact while pushing the boundaries of what's possible in next-generation intelligent systems.

• Lead the design and evolution of end-to-end AI and Agentic AI architectures that enable innovation at enterprise scale.

• Shape the Hub's technical vision, translating strategic objectives into coherent, high-impact architectures.

• Act as a technical authority, ensuring quality, scalability, and security are embedded into every solution.

• Guide multidisciplinary teams - from data scientists to engineers - toward architectural excellence and delivery of real business value.

• Bridge the gap between business strategy and technology, ensuring every initiative aligns with both innovation and operational goals.

• Foster a culture of technical rigor, creativity, and responsible AI, where emerging technologies are tested, adopted, and turned into value.

• Collaborate with leadership to define the technological roadmap of the Hub and ensure alignment with global best practices in AI engineering.

• Mentor and inspire others, creating an environment where ideas evolve into architectures that shape the future of enterprise AI.

• 7+ years of experience designing and delivering large-scale AI or ML architectures in complex enterprise environments.

• Proven ability to design and implement end-to-end AI ecosystems - from data pipelines and model training to deployment and monitoring.

• Deep knowledge of AI and ML architectures, cloud-native solutions, and/or distributed systems.

• Expertise in at least one major cloud provider (Azure, AWS, GCP) and associated AI platforms (e.g., Azure ML, Vertex AI, OpenShift AI, Databricks).

• Solid understanding of MLOps frameworks (MLflow, Kubeflow, Airflow) and container orchestration (Kubernetes, Docker).

• Familiarity with multi-agent frameworks (LangGraph, CrewAI, AutoGen, Google ADK) and RAG architectures (LangChain, LlamaIndex).

• Demonstrated leadership skills, with the ability to drive architectural direction and influence cross-functional technical teams.

• Bachelor's or Master's degree in Computer Engineering, Artificial Intelligence, Data Science, or related technical field.

• Advanced studies (Master's or PhD) in AI, Machine Learning, or Cloud Architecture are highly valued.

• Professional certifications in cloud architectures (Azure, AWS, or GCP) and MLOps frameworks are a strong plus.

• Continuous learning mindset with proven commitment to staying current on emerging AI and Agentic AI technologies.

• Experience designing hybrid or federated architectures integrating LLMs, APIs, and enterprise data sources.

• Knowledge of observability, monitoring, and FinOps best practices in AI workloads.

• Hands-on experience with vector databases, semantic search, or LLM optimization techniques.

• Exposure to edge AI or on-premise AI deployments in regulated industries.

• Strong foundation in data governance, security, and regulatory compliance (GDPR, EU AI Act, Responsible AI principles).

• Strong presentation and storytelling skills to articulate architectural visions to both technical and executive audiences.

• Passion for exploring emerging AI technologies, assessing their maturity, and driving their adoption in real-world scenarios.

• Proven track record mentoring teams and fostering a culture of innovation, collaboration, and technical excellence.

• Experience leading multidisciplinary technical teams, ensuring alignment between innovation, performance, and compliance.

• Knowledge of Responsible AI frameworks, data governance, and AI observability.

• Strong communication and synthesis skills, with the ability to explain complex technical concepts clearly to both technical and non-technical audiences.

• Translational mindset - capable of understanding functional and business needs and converting them into actionable, scalable technical solutions.

• Analytical and structured thinking, with a focus on solving complex problems through robust, pragmatic architectures.