Senior AI Engineer (M/F)

Arche Consulting Sp. z o.o.; Warszawa; On-site; PLN 180,000 - 240,000; Full time

Job summary

Arche Consulting Sp. z o.o. represents a client driving a large-scale digital transformation with cloud adoption and microservices architecture modernization.

The role focuses on designing and implementing AI-powered solutions for software development, integrating AI tools in DevOps environments, and building AI agents and workflows for engineering teams. You will engage with developers, managers, and stakeholders to deliver high-value AI outcomes.

Qualifications

• 5+ years in a technical role within software development
• Hands-on experience with AI tools across SDLC
• Experience in AI-driven automation and architecture
• Ability to translate business needs into technical initiatives

Responsibilities

• Design and implement AI-powered solutions that support software development processes
• Configure, integrate, and enhance AI tools within development and DevOps environments
• Build AI agents, workflows, prompts, and reusable skills for engineering teams
• Integrate AI with repositories, CI/CD pipelines, code reviews, and testing frameworks
• Provide hands-on engineering support and collaborate with development teams
• Lead technical workshops and identify AI adoption opportunities across the organization
• Define and standardize AI usage practices and engineering workflows across teams
• Monitor AI implementations and recommend continuous improvements
• Prepare technical documentation and support knowledge transfer
• Collaborate with engineers, managers, and business stakeholders to deliver high-value AI solutions

Skills

AI/ML concepts

DevOps experience

SDLC knowledge

Requirements translation

Engineering collaboration

English communication

Tools

GitHub Copilot

Cursor

Claude Code

Codex

M365 Copilot

Job description

Our client is leading a large-scale digital transformation initiative focused on modernizing enterprise systems, driving cloud adoption, and evolving business-critical applications toward scalable, microservices-based architecture.

Responsibilities

• Designing and implementing AI-powered solutions that support software development processes,
• configuring, integrating, and enhancing AI tools within development and DevOps environments,
• building AI agents, workflows, prompts, and reusable skills tailored to engineering teams,
• integrating AI solutions with repositories, CI/CD pipelines, code review processes, and testing frameworks,
• providing hands-on engineering support and collaborating directly with development teams,
• leading technical workshops and identifying opportunities for AI adoption across the organization,
• defining and standardizing AI usage practices and engineering workflows across multiple teams,
• monitoring the effectiveness of AI implementations and recommending continuous improvements,
• preparing technical documentation and supporting knowledge transfer initiatives,
• collaborating with engineers, managers, and business stakeholders to deliver high-value AI solutions.

Requirements

• Minimum 5 years of experience in a technical role such as Software Developer, DevOps Engineer, QA Automation Engineer, or similar,
• hands-on experience working within software development teams and across the full application lifecycle,
• practical experience implementing AI tools that support SDLC processes, including GitHub Copilot, Cursor, Claude Code, Codex, M365 Copilot, or similar solutions,
• experience designing and building AI agents, workflows, prompts, skills, and automation solutions,
• strong understanding of LLMs, RAG architectures, agentic systems, and AI-driven automation,
• experience integrating AI solutions into engineering ecosystems and software delivery processes,
• knowledge of Spec-Driven Development and modern AI-assisted software engineering practices,
• ability to gather and translate business and technical requirements into implementation initiatives and solution architecture,
• experience evaluating AI business value, measuring adoption outcomes, and optimizing model usage costs,
• excellent communication and consulting skills with the ability to engage technical teams, managers, and senior stakeholders,
• English proficiency at a minimum B2 level.