Senior Modernization Engineer (FDE)

Kyndryl specializes in operating and transforming mission-critical technology systems for leading global businesses, with a focus on AI-powered insights and enterprise AI deployments. The role is within a triad delivery model combining engineering, consulting, and product expertise to deliver AI solutions with real-world impact.

• Bachelor’s degree in Computer Science, Engineering, or equivalent.
• Hands-on experience with Python development and frontend UI technologies (e.g., TypeScript, React.js).
• Experience building AI solutions using AI frameworks such as LangChain, Microsoft Semantic Kernel, Google ADK, or Microsoft Agent Framework.
• Knowledge of LLMs, AI Agent architectures, and Agent Telemetry/Observability frameworks (e.g., Langsmith, Langfuse, litellm).
• Expertise with Docker, Kubernetes, and at least one cloud platform (Azure, AWS, GCP) or on-premises.
• Experience with microservices-based architectures.
• Understanding of software delivery lifecycle, version control (Git, GitHub), and data engineering tools like Pandas and Spark.
• Experience with cloud AI platforms (AWS AI, Azure AI, Google AI) and distributed computing.
• Ability to translate business requirements into technical solutions and communicate to stakeholders.
• Experience with SQL databases (e.g., PostgreSQL), NoSQL (e.g., MongoDB), and vector databases for semantic queries.
• Proficiency in CI/CD tools (e.g., 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.
• Practical knowledge of deploying RAG architectures and integrating structured and unstructured data.
• Familiarity with open-source AI ecosystems, including Hugging Face.
• Deep technical expertise in select domains with broad AI/ML, cloud, and consulting knowledge.
• Experience designing, building, or 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.

• Building autonomous agents using LLMs, planning algorithms, and decision-making frameworks.
• Implementing agent architectures that support autonomy, interactivity, and task completion.
• Integrating agents into applications, APIs, and workflows such as copilots and chatbots.
• Connecting agents to external services via APIs, databases, and cloud platforms.
• Tuning agent behavior using feedback loops, reinforcement learning, semantic knowledge layers, and user interaction.
• Monitoring performance and implementing safety, reliability, and guardrail mechanisms.
• Collaborating cross-functionally with researchers, engineers, and product teams.
• Documenting agent logic, design decisions, and dependencies clearly.
• Building and maintaining the Enterprise Agents and Tools Registry.
• Implementing the Agent Communication Gateway with security, rate limits, observability, and cost controls.
• Applying AI Agent orchestration patterns and workflow engines like Temporal and Airflow.
• Ensuring agent-level security including authentication, authorization, and data protection.
• Optimizing cost, scalability, performance, and reliability across cloud and on-premises environments.
• Utilizing knowledge graphs for agent reasoning and data integration.
• Deploying and customizing agentic AI platforms and orchestration frameworks.
• Integrating AI systems with enterprise APIs, data platforms, and workflows.
• Solving technical blockers in data ingestion, model deployment, and agent behavior.
• Designing and refining prompts for clarity, compliance, and contextual accuracy.
• Translating business logic into agentic workflows and task trees.
• Implementing observability tools to ensure reliability, latency, and trustworthiness.
• Maintaining performance metrics and continuous feedback loops.
• Building custom AI solutions tailored to customer needs.
• Owning delivery end to end from scoping to production.
• Contributing to the evolution of Kyndryl’s AI platforms through feedback and code contributions.
• Partnering with customers to deliver fit-for-purpose technical solutions prioritizing outcomes.
• Troubleshooting and enhancing system performance, scalability, and reliability.
• Capturing deployment learnings and sharing insights to improve core platforms.
• Engaging in continuous professional development adapting to emerging technologies.

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