Full Stack Engineer
Confirmed on the employer's own hiring board on Oct 12, 2026. First seen by Alion on Sep 30, 2026.
Join Liberty Global as a Full Stack Engineer and play a key role in designing, building, and evolving AI-first telecom platforms that serve millions of customers across multiple countries. You will work closely with the VP Software Engineering and the wider platform team to translate architectural direction into working software, challenge technical assumptions, and raise the engineering bar across the organization. Your responsibilities will include designing and owning critical platform components, evaluating and proposing solutions to complex technical challenges, writing production-quality code, and championing engineering best practices.
Missions
- Design, build, and evolve AI-first telecom platforms, ensuring scalability, security, and readiness for enterprise-scale demands.
- Lead architecture reviews and technical design sessions, defining integration patterns and data flows across platform services.
- Write production-quality code across the full stack, delivering features and platform capabilities end to end, from design through deployment.
Profil recherché
- Experience working with cloud-native infrastructure (AWS, GCP or Azure) and container orchestration (Kubernetes or equivalent)- Strong experience in code and architecture review - giving and receiving feedback that improves the work
- Proven ability to translate complex architectural requirements into clear, deliverable engineering plans
- Experience collaborating with or reviewing the output of SI / vendor build partners
- Comfortable working in fast-paced delivery environments with clear prioritisation and a bias for shipping
- Exp of hands-on full stack engineering experience, delivering complex platforms in enterprise environments
- Strong proficiency across the full stack - backend (Python, Java or equivalent), frontend frameworks, APIs, databases and infrastructure as code
- Depth in distributed systems design: you understand how to build services that scale, fail gracefully and recover quickly
- Balances doing things right with doing things fast - pragmatic about trade-offs, clear about where corners cannot be cut
- Goes deep into complex problems - doesn’t stop at the surface, finds the right answer and explains why
- Consistently makes sound technical decisions, balancing short-term delivery with long-term platform health
- Owns their delivery end to end and takes pride in shipping things that work, not just things that are finished
- Makes engineering standards better by making them practical - not just written, but followed
- Shares knowledge generously: documentation, pairing, review - builds the team up, doesn’t hoard expertise
- Holds themselves and others to a high bar on code quality, security and production readiness
- Works effectively across teams - engineering, product, build partners - and communicates technical decisions clearly
- Experience building or contributing to AI/ML platforms - particularly integrating LLMs, speech, or multimodal models into production systems
- Familiarity with data pipelines, data quality processes and the infrastructure that supports AI/ML at scale
- Exposure to telecom or large-scale consumer-facing platforms
- Experience with DevOps, CI/CD pipelines and observability tooling