Senior AI Engineer

Quick Facts

• Role: Senior AI Engineer (GenAI, AI Agents, Agentic SDLC)
• Focus: Building and integrating AI solutions into the software development lifecycle
• Work model: Hybrid (minimum 1 day/week in the office)
• Collaboration: Pair/mob programming, discovery workshops, and knowledge transfer

Description

You will support IT teams in the practical use of artificial intelligence in software manufacturing. The role combines software engineering experience with GenAI, AI Agents, and Agentic SDLC capabilities—covering discovery, workflow design, integration into the existing environment, production deployment, and knowledge transfer.

Responsibilities

• Implement and integrate AI tools into the software development environment
• Design and build AI workflows, agents, prompts, and automation
• Integrate AI solutions with repositories, CI/CD, code review, and testing processes
• Support IT teams in applying AI in daily work
• Design and evolve Agentic SDLC practices for roles such as Developer, QA, Analyst, and DevOps
• Run technical workshops and discovery activities
• Translate business and technical needs into solutions and architecture
• Productionly deploy AI solutions (configuration, integration, hardening, monitoring)
• Analyze AI deployment effectiveness and optimize model usage costs
• Collaborate in pair/mob programming, including joint design and code review
• Prepare technical documentation and AI usage standards
• Transfer knowledge and help teams take ownership of deployed solutions

Requirements

• Minimum 5 years in a technical role (e.g., Software Developer, DevOps Engineer, QA/Test Automation Engineer or similar)
• Practical experience in software development teams and full SDLC knowledge
• Hands-on experience using AI tools for software development (e.g., GitHub Copilot, Claude Code, Cursor, Codex, M365 Copilot or open-source models)
• Practical knowledge of building AI Agents, AI Workflows, skills, and prompts
• Experience integrating AI solutions into the production environment: repositories, CI/CD, code review, and testing
• Knowledge of Spec-Driven Development and modern AI-supported software engineering practices
• Knowledge of LLM, RAG, automation, and agent architecture
• Experience with production deployment of AI solutions including configuration, integration, hardening, and monitoring
• Ability to translate business and technical needs into concrete solutions and architecture
• Ability to evaluate business value of AI solutions and optimize model costs
• Excellent communication and consulting skills; experience collaborating with both technical teams and management
• Experience transferring knowledge through pair/mob programming and joint code review
• Availability for hybrid work: at least 1 day per week in the office
• Experience providing services from the territory of Poland

Benefits

• Long-term collaboration on a project focused on practical AI use
• Opportunity to work on solutions covering GenAI, AI Agents, and Agentic SDLC
• High autonomy in designing and deploying solutions
• Hybrid model: 1 day in the office
• Access to Luxmed and Multisport package on preferential terms