Modernization Engineer (FDE)

Kyndryl is a company deploying AI innovation to mission-critical technology systems for leading global businesses. It operates with a triad delivery model integrating engineering, consulting, and product expertise to deliver transformative AI solutions. The role is based in Wroclaw, Poland, at Kyndryl Global Services Delivery Centre Polska Sp. z o.o.

• Bachelor’s degree in computer science, Engineering, or equivalent.
• Hands-on experience with Python development and frontend UI technologies such as TypeScript and React.js.
• Experience building AI solutions using AI frameworks like LangChain, Microsoft Semantic Kernel, Google ADK, or Microsoft Agent Framework.
• Knowledge of LLMs, AI Agent architectures, and telemetry/observability frameworks like Langsmith, Langfuse, litellm.
• Expertise with Docker, Kubernetes, and at least one cloud platform (Azure, AWS, or GCP) or on-premises.
• Experience in microservices-based architectures.
• Solid understanding of software delivery lifecycle, version control (Git, GitHub), and data engineering tools such as Pandas and Spark.
• Experience with cloud AI platforms (AWS AI, Azure AI, Google AI) and distributed computing architectures.
• Ability to translate business requirements into technical solutions and communicate value to stakeholders.
• Hands-on experience with SQL (e.g., PostgreSQL), NoSQL (e.g., MongoDB), and vector databases.
• Proficiency with CI/CD tools such as GitHub Actions, automated testing, and observability.
• Familiarity with agent-based modeling, multi-agent systems, or reinforcement learning.
• Proficiency in API development, backend services, and cloud platforms (AWS, Azure, GCP).
• Practical knowledge of deploying RAG architectures and integrating structured and unstructured knowledge sources.
• Familiarity with open-source AI tools and libraries including Hugging Face.
• Experience designing/integrating multi-agent systems and orchestration frameworks (e.g., LangGraph, Semantic Kernel, Agent Framework, AutoGen, CrewAI).
• Knowledge of system-level optimization and security best practices for scalable AI systems.
• Willingness to travel up to 25% globally.

• Build autonomous agents using LLMs, planning algorithms, and decision-making frameworks.
• Implement agent architectures supporting autonomy, interactivity, and task completion.
• Integrate agents into applications, APIs, and workflows such as copilots, chatbots, and automation tools.
• Connect agents to external services via APIs, databases, and cloud platforms.
• Tune agent behavior with feedback loops, reinforcement learning, semantic knowledge layers, and user interaction.
• Monitor performance and implement safety, reliability, and guardrail mechanisms.
• Collaborate cross-functionally with researchers, engineers, and product teams.
• Document agent logic, designs, decisions, and dependencies clearly.
• Build and maintain the Enterprise Agents and Tools Registry for metadata and lifecycle management.
• Implement the Agent Communication Gateway with robust security, rate limits, observability, and cost controls.
• Ensure agent-level security, including authentication, authorization, and data protection.
• Optimize cost, scalability, performance, and reliability of agent operations across cloud and on-premises environments.
• Deploy and customize agentic AI platforms, including LLM agents and orchestration frameworks.
• Integrate AI systems with enterprise APIs, data platforms, and workflows.
• Solve technical blockers across data ingestion, model deployment, and agent behavior.
• Design and refine prompts to ensure clarity, compliance, and contextual accuracy.
• Translate business logic into agentic workflows and task trees.
• Implement observability tools to ensure reliability, latency, and trustworthiness.
• Maintain performance metrics and feedback loops for continuous improvement.
• Build and iterate custom AI solutions tailored to customer needs leveraging agentic AI frameworks.
• Own delivery end to end, from scoping to production, working as part of the customer team.
• Actively contribute to the evolution of Kyndryl’s AI platforms through feedback, code contributions, and collaboration.
• Partner with customers to understand challenges and translate them into high-quality solutions.
• Troubleshoot and optimize system performance, scalability, and reliability.
• Capture deployment learnings, document best practices, and share insights to enhance Kyndryl’s platforms.
• Engage in ongoing professional development to stay current with emerging technologies.

Information on reporting breaches of law at Kyndryl is provided in connection with the Whistleblower Protection Act of June 14, 2024.