AI Engineer (Python)
Summary
Builds and tunes AI agent workflows, prompts, and tools that analyze legacy code and migrate it to modern, platform-approved stacks, integrated with CI/CD (Tekton, ArgoCD, Ansible). Python-heavy engineering role, hybrid with 2-3 days/week in the Gdynia office; B2B rate 155 PLN/h.
Rate: 155 pln/h net + VAT, B2B
Work model: hybrid (2-3 days per week from office Gdynia)
Overview
We are seeking a skilled engineer to join our team focused on building a Tech Modernization Framework. This framework utilizes AI to analyze legacy code repositories and reimplement them onto our contemporary, platform-approved technology stacks. The selected candidate will be responsible for designing and optimizing the agent workflows, prompts, and tools that facilitate these migrations, integrating them with our CI/CD and deployment platforms (Tekton, ArgoCD, Ansible).
Main Responsibilities
Design and improve agent workflows for code migration.
Integrate AI-driven tools with existing CI/CD pipelines.
Collaborate with application teams to convert migration cases into efficient automation processes.
Analyze legacy code to ensure successful migration.
Maintain clean and maintainable code standards throughout the project.
Key Requirements
Strong programming skills in Python.
Solid understanding of software engineering fundamentals: Git, code review, testing, clean and maintainable code.
Working knowledge of CI/CD concepts and containerized environments (Docker, Kubernetes basics).
Hands-on experience with, or a strong interest in, LLMs and AI-assisted development.
Able to read and understand code in multiple languages, including legacy code (e.g., Java).
Analytical and structured problem-solving skills, comfortable with ambiguity and experimentation.
Good communication skills in English and a collaborative attitude.
Nice to Have
Experience with Tekton, ArgoCD or other GitOps/pipeline tools.
Familiarity with Ansible or similar infrastructure-as-code tools.
Experience with agentic coding tools (Claude Code or similar) and agent frameworks.
Knowledge in LLM evaluation, context engineering, or the Model Context Protocol (MCP).
Background in legacy modernization, code migration, or large-scale refactoring.
Familiarity with Java/Spring, front-end stacks, or other target technologies.
Experience in a regulated or enterprise environment (e.g., banking).
