AI Engineer

Quick Facts

• Role: AI Engineer (project-based)

• Focus: Implementing and embedding AI tools to support the software development lifecycle (SDLC) in IT delivery teams

• Collaboration: Coordination meetings in the partner’s Warsaw office once per week; otherwise remote

Description

The project focuses on configuring and deploying AI tools and solutions that support the SDLC across software delivery teams. You will build and integrate AI workflows, agents, skills, and prompts into repositories, CI/CD, code review, and testing, while preparing standards and technical documentation so teams can independently maintain and evolve the solutions. You will also provide ongoing engineering support (e.g., pair/mob programming), run discovery workshops, and translate business/technical needs into architecture and deployment initiatives.

Responsibilities

• Configure and deploy AI tools in software delivery team environments

• Create AI workflows, agents, skills, and prompts and embed them into repositories, CI/CD processes, code review, and tests

• Prepare AI usage standards and technical documentation for teams

• Provide ongoing engineering support to teams using the deployed solutions (pair/mob programming, shared code review)

• Organize technical workshops to identify needs (discovery) and translate them into concrete implementation initiatives

Requirements

• Minimum 5 years of technical experience in a software/engineering role (e.g., Software Developer, DevOps Engineer, QA/Test Automation Engineer or similar)

• Experience gained in software delivery/production teams

• Knowledge of the full application lifecycle (SDLC)

• Experience designing and deploying AI tool–based solutions in SDLC (e.g., GitHub Copilot, Claude Code, Cursor, Codex, M365 Copilot, open-source models)

• Ability to build and operationalize AI agents, workflows, skills, and prompts in the delivery environment (repositories, CI/CD, code review, tests)

• Knowledge of Spec-Driven Development and current AI-supported software engineering practices

• Knowledge of LLMs, RAG, automation, and agent architecture

• Experience deploying AI solutions to production (configuration, integration with enterprise systems, hardening, monitoring, iterative development)

• Ability to gather and structure business and technical needs and translate them into initiatives and solution architecture (including via discovery workshops)

• Ability to evaluate business value, optimize model costs, and measure the effects of deployments

• Strong communication and consulting skills for discussions with technical teams and management

• Experience transferring engineering knowledge through pair/mob programming, joint code reviews, and co-design/co-build on real tasks

• Ability to establish consistent internal practices for working with AI tools and to tailor Agentic SDLC practices to roles (developer, tester, analyst, DevOps)

Benefits

• Project-based collaboration with stage-based billing and acceptance protocols for deliverables

• Flexible B2B cooperation model

• Engineering and administrative support for collaboration and billing

• Participation in industry events and technology meetups

• Opportunity for referral bonus (PLN 5,000)

• Quick and remote recruitment process