Senior AWS Network Engineer

Xebia is a global AI-first, digital transformation, and engineering partner. With over 25 years of experience and a team of 5,000 professionals across 16 countries, we help organizations design and build scalable products, platforms, and data-driven solutions.

We specialize in Artificial Intelligence, Data and Cloud, Intelligent Automation, and Digital Products, combining deep technical expertise with a strong focus on engineering excellence and a people-first culture.

In the CEE region, we’re a team of nearly 1,000 experts delivering modern applications, data platforms, and AI solutions for clients such as McLaren, Aviva, Deloitte, Spotify, Disney, ING, UPS, Tesco, Truecaller, AllSaints, Volotea, Schmitz Cargobull, Allegro, InPost, and many, many more. We work with leading technologies including AWS, Azure, GCP, Databricks, and Snowflake, and combine strong engineering culture with a consulting mindset and a continuous focus on growth and knowledge sharing.

You will be:

• delivering the entire global network backbone infrastructure across multiple AWS regions,
• building centralised egress architectures using AWS Network Firewall to ensure secure, scalable, and cost-effective traffic management across all regions,
• building and maintaining AWS Cloud WAN infrastructure to provide seamless connectivity and routing across the global network footprint,
• developing and maintaining infrastructure as code using Terraform to ensure consistent, repeatable, and version-controlled network deployments,
• collaborating with security architects, cloud engineers, and other stakeholders to gather requirements and translate them into robust network architectures and technical specifications,
• driving the implementation of network automation and self-service capabilities to enable parallel development and incremental delivery of network services,
• leading by example through hands-on technical work while mentoring other network engineers and providing technical guidance and knowledge sharing,
• ensuring the reliability, performance, and security of network infrastructure through comprehensive testing, monitoring, and continuous improvement,
• driving the adoption of best practices in network engineering, including infrastructure as code and automation-first approaches,
• troubleshooting and resolving complex network issues across multi-region environments on time,
• staying up to date with the latest AWS networking services, industry trends, and technologies to ensure the infrastructure remains competitive and efficient.

Your profile:

• 5+ years of experience in network engineering with a strong focus on enterprise cloud networking solutions,
• practical experience using AI-powered assistants (e.g. Claude Code, GitHub Copilot, Cursor) to improve productivity, quality, or decision-making in software delivery,
• deep hands-on expertise in AWS Cloud WAN, including configuration, routing policies, and multi-region connectivity,
• strong proficiency in Terraform and proven experience managing complex network infrastructure deployments,
• extensive experience designing and implementing centralised egress architectures using AWS Network Firewall, including policy management and traffic inspection,
• proven track record of delivering large-scale network infrastructure projects in fast-paced environments,
• excellent problem-solving skills with the ability to think critically and creatively about complex network challenges,
• strong communication and collaboration skills with the ability to work effectively in cross-functional and team-oriented environments,
• experience working with agile methodologies and DevOps practices applied to network infrastructure,
• ability to use a data-driven approach to network optimisation, capacity planning, and decision-making,
• fluent English communication skills.

Work from the European Union region and a work permit are required.

Nice to have:

• experience applying GenAI in a more structured way within the SDLC, including defined workflows, prompt patterns, or tool integrations embedded into daily work,

• interest in and familiarity with emerging AI-driven practices (e.g.