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
At Kyndryl, we deploy AI innovation where it creates the greatest real-world impact. As an AI Forward Deployed Engineer, you will collaborate directly with customers to solve complex challenges, shaping solutions that redefine industries. Working within our triad delivery model - where engineering, consulting, and product expertise come together - you will operate in dynamic environments to scope, prototype, and deploy production-ready AI solutions at pace.
This is a hybrid role designed for the complexities of enterprise AI deployment, blending deep backend engineering with client-facing consultative engagements to deliver measurable business outcomes. Insights gained in the field will continuously feed back into Kyndryl’s core platforms to accelerate future deployments.
What you will do
Collaborate directly with customer teams on-site and remotely to own end-to-end delivery from scoping to production deployment.
Design, build, and deploy autonomous AI agents, multi-agent systems, and workflow orchestration engines into enterprise APIs and applications.
Develop and maintain core agent architecture components, including Enterprise Agent Registries, Communication Gateways, and semantic knowledge layers.
Implement AI telemetry, observability, and evaluation mechanisms using tools such as LangSmith and Langfuse to monitor latency, performance, and trustworthiness.
Establish enterprise guardrails, agent-level security, authentication, data protection, and cost/scalability optimization across cloud and on-premises environments.
Solve complex technical blockers across data ingestion, prompt engineering, fine-tuning, and real-world system performance.
Systematically capture deployment learnings, best practices, and code contributions to inform enhancements to Kyndryl’s core AI platform ecosystem.
Your future at Kyndryl
This role opens doors to versatile career paths across engineering, architecture, and technical leadership. It serves as a solid foundation to progress into roles such as Enterprise Architect, Chief Architect, or Distinguished Engineer. Wherever you see your future, you will find continuous opportunities for growth and impact at Kyndryl.
Who You Are
Required skills and experience
Bachelor’s degree in Computer Science, Engineering, or equivalent practical experience.
Strong hands-on experience in Python development, microservices, backend API design, and core software delivery practices (Git, CI/CD).
Proven experience building production AI/LLM-based solutions and multi-agent systems using frameworks like LangChain, LangGraph, Microsoft Agent Framework, or Google ADK.
Strong understanding of core AI architecture concepts, including Retrieval-Augmented Generation (RAG), Model Context Protocol (MCP), vector databases, tool/function calling, prompt engineering, and agent orchestration.
Practical experience with containerization and cloud platforms (Docker, Kubernetes, Azure, AWS, or GCP).
Experience with AI observability, evaluation, and telemetry frameworks (e.g., LangSmith, Langfuse, LiteLLM).
Demonstrated understanding of AI safety, guardrails, data protection, and performance/cost optimization for enterprise AI systems.
Ability to translate business requirements into technical architectures and communicate technical value effectively to both technical and executive stakeholders (willingness to travel up to 25%).
Preferred skills and experience
Familiarity with data engineering…