As a Agentic AI Engineer at Kyndryl you are the bridge between business problems and innovative solutions, using a powerful blend of well-defined methodologies, statistics, mathematics, domain expertise, consulting, and software engineering.
You'll wear many hats, and each day will present a new puzzle to solve, a new challenge to conquer.
Embark on a transformative process of business understanding, data understanding, and data preparation.
Create models that defy convention, holding the key to solving intricate business challenges.
Evaluate models to ensure they not only solve business problems but do so optimally.
Deploy models as code to applications and processes, ensuring that the selected model(s) sustain their business value throughout their lifecycle.
Navigate business processes, identify issues and craft solutions that drive meaningful change in these domains.
Develop and apply standards and policies that protect data security, privacy, accuracy, availability, and usability.
Orchestrate the end-to-end process: business understanding, system design, and deployment of AI agents capable of handling real-world complexity.
Engineer solutions that autonomously adapt, learn, and optimize, evaluating them for scalability, safety, and reliability in production.
Integrate and operationalize agentic AI into applications, workflows, and processes, ensuring continuous value delivery.

6+ Yrs Hands-on experience building and deploying agentic AI systems , autonomous workflows, or multi-agent orchestration solutions with total exp of 8-12 years.
Proficiency in AI/ML development tools and languages such as Python, LangChain, LlamaIndex, Hugging Face, or orchestration frameworks like Azure AI Studio, Prompt Flow, AutoGen, or CrewAI.
Strong problem-solving, analytical, and reasoning skills , with the ability to translate complex business challenges into agentic workflows.
Excellent communication and storytelling abilities , capable of conveying complex AI concepts and system behaviors to both technical and non-technical stakeholders.
Ability to manage and deliver multiple AI initiatives simultaneously , maintaining precision and quality across the lifecycle—from design to deployment.

AI Engineer

Key skills