AI Engineer - Agentic AI Solutions

About the role

Kyndryl is hiring an AI Engineer (Modernization Engineer) to work directly with customers on complex challenges and build solutions that reshape industries. The hybrid role combines engineering depth with consultative skills, focusing on real-world AI deployment and accountability for outcomes rather than just code. You will work closely with customer teams, often on-site, to scope, prototype and deploy generative AI, agentic AI and multi-agent solutions.

Key responsibilities

• Build autonomous agents using Kyndryl's Agentic Platform, LLMs, planning algorithms and decision frameworks, and customise pre-built agents for scale and consistency.
• Design agent architectures and integrate agents with applications, APIs, workflows, databases, cloud platforms and external services.
• Refine agent behaviour through feedback loops, reinforcement learning and user interactions, and monitor performance with safeguards for security and reliability.
• Collaborate with researchers, engineers and product teams, document agent logic and design decisions, and maintain the Enterprise Agents and Tools Registry.
• Implement the Agent Communication Gateway with security, rate limiting, observability and cost controls, and use orchestration tools such as Temporal and Airflow.
• Protect agents with authentication, authorisation and data security controls, and optimise cost, scalability and performance across cloud and on-premises environments.
• Use knowledge graphs to strengthen agent reasoning, and deploy and tailor agentic AI platforms, LLM agents and orchestration frameworks.
• Resolve blockers in data ingestion, model deployment and agent behaviour, design and refine prompts, and build customer-specific AI solutions.
• Own delivery from scoping through production, embed with customer teams, and capture deployment lessons to improve Kyndryl's platforms.

Required profile

• Bachelor's degree in computer science, engineering or an equivalent field.
• Full-stack development experience with Python and front-end technologies such as TypeScript and React.js, including building demos and systems from the ground up.
• Minimum 3 years of hands-on experience building AI solutions with frameworks such as LangChain, Microsoft Semantic Kernel, Google ADK or Microsoft Agent Framework.
• Knowledge of LLMs, agent architectures and telemetry/observability tools such as LangSmith, Langfuse and LiteLLM.
• Experience with microservices architectures, the software delivery lifecycle, Git and GitHub, and data engineering tools such as Pandas and Spark.
• Ability to translate business needs into technical solutions and explain their value to stakeholders, including executives.
• T-shaped profile: deep expertise in one or two areas, with broad knowledge of AI/ML, cloud and consulting.

Required skills

• Docker, Kubernetes and at least one cloud platform (Azure, AWS or GCP) or on-premises environments.
• Hands-on experience with SQL (PostgreSQL), NoSQL (MongoDB) and vector databases.
• CI/CD tools such as GitHub Actions, automated testing and observability.
• API development, back-end services and cloud AI platforms.
• Practical experience deploying RAG architectures and integrating structured and unstructured knowledge sources.
• Familiarity with open-source AI tools such as Hugging Face.
• Experience with multi-agent systems and orchestration frameworks such as LangGraph, Semantic Kernel, Agent Framework, AutoGen or CrewAI.

What we offer

• A hybrid-friendly culture with flexible, supportive working conditions.
• Career paths from Junior to Principal, with opportunities to lead engagements and shape strategy.
• Learning opportunities including certifications with Microsoft, Google and Amazon, coaching and hands-on experiences.
• Well-being programmes covering financial, mental, physical and social health.