Senior Modernization Engineer (FDE)

At Kyndryl (Permanent), in Wrocław, Poland

Expires at: 2027-01-17

Remote policy: Partial remote

Key Responsibilities

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 (e.g., copilots, chatbots, automation tools).

Connecting agents to external services via APIs, databases, and cloud platforms.

Tuning agent behavior using feedback loops, reinforcement learning, semantic knowledge layer and user interaction.

Monitoring performance and implementing safety, reliability, and guardrail mechanisms.

Working cross-functionally with researchers, engineers, and product teams.

Maintaining clear documentation of agent logic, designing decisions, and dependencies.

Building and maintaining the Enterprise Agents and Tools Registry for metadata and lifecycle management.

Implementing the Agent Communication Gateway with robust security, rate limits, observability, and cost controls.

Familiarity with AI Agent orchestration patterns and workflow orchestration engines (e.g., Temporal, Airflow, etc.).

Ensuring agent-level security, including authentication, authorization, and data protection.

Optimizing cost, scalability, performance, and reliability of agent operations across cloud and on-prem environments.

Familiarity with knowledge graphs for agent reasoning and data integration.

Deploying and customizing agentic AI platforms (e.g., LLM agents, orchestration frameworks).

Integrating AI systems with enterprise APIs, data platforms, and workflows.

Solving technical blockers across data ingestion, model deployment, and agent behavior.

Designing and refining prompts to ensure clarity, compliance, and contextual accuracy.

Translating business logic into agentic workflows and task trees.

Tuning agent behavior to align with real-world expectations.

Implementing observability tools to ensure reliability, latency, and trustworthiness.

Maintaining performance metrics and feedback loops for continuous improvement.

Building and iterating custom AI solutions tailored to customer needs, leveraging agentic AI frameworks

Owning delivery end to end, from scoping to production. Working as part of the customer team to engineer and deploy production-ready solutions that drive adoption and measurable business outcomes.

Actively contributing to the evolution of Kyndryl’s AI platforms through feedback, code contributions, and collaboration with product team

Customer Engagement & Solution Integrity: Partnering with customers to understand business

Main requirements

Bachelor’s degree in computer science, Engineering, or equivalent.

Hands-on experience with Python development and frontend UI technologies (e.g., TypeScript, React.js, etc.) to build demos/systems from scratch as a full stack engineer.

Hands-on experience building AI based solutions using AI frameworks such as LangChain, Microsoft Semantic Kernel, Google ADK or Microsoft Agent Framework.

Knowledge of LLMs, AI Agent architectures, Agent Telemetry/Observability frameworks (Langsmith, Langfuse, litellm etc).

Expertise with Docker, Kubernetes, and at least one cloud platform (Azure, AWS, GCP) or on premises.

Experience in microservices-based architectures.

Solid grasp of the software delivery lifecycle, version control (Git & GitHub), and data engineering tools such as Pandas and Spark.

Experience with cloud AI platforms (AWS, Azure, Google AI) and distributed computing architectures.

Ability to translate business requirements into technical solutions and communicate technical value to diverse stakeholders, including executive audiences.

Hands-on experience with SQL (e.g., PostgreSQL), NoSQL (e.g., MongoDB), and vector databases for agent data storage, semantic queries and retrieval.

Proficiency in CI/CD (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 (AWS, Azure, GCP).

Practical knowledge of deploying RAG architectures and integrating structured and unstructured knowledge sources into AI solutions.

Open-Source Ecosystems: Familiarity with community-driven AI tools and libraries, including Hugging Face and relevant repositories.

T-shaped Profile: Deep technical expertise in one or two domains, with broad understanding across AI/ML, cloud, and consulting.

Agentic AI Systems: Experience designing, building, or integrating multi-agent systems and orchestration frameworks (e.g., LangGraph, Semantic Kernel, Agent Framework, AutoGen, CrewAI), including the development of agent protocols and coordination mechanisms.

Performance & Security: Knowledge of system-level optimisation and security best practices for scalable AI systems.

Willingness to travel up to 25% globally.

Benefits & Perks

Private health card

Life insurance package

Multisport Card

Discounts for Kyndryl employees

A wide range of benefit options for parents and children

Sports activities and team events

Free language courses & many personal development possibilities

Employee referral program

Mindfulness and Yoga Classes