DevOps Architect

Join our Team About this opportunity At Ericsson, we're passionate about building software that solves problems. As a DevOps leader, you will lead a team of developers delivering DevOps, CI/CD and automation solutions for Ericsson's 4G and 5G product portfolio, implemented in customer networks across different business cases.

What you will do

Lead technical design discussions, architecture reviews and proof-of-concept initiatives. Gather and analyze metrics from operating systems and applications to support performance tuning and fault finding. Partner with development teams to improve services through rigorous testing and release procedures. Participate in system design consulting and platform management.

Create sustainable systems and services through automation and uplifts. Balance feature development speed and reliability with well-defined service level objectives. Roll out automation in customer environments and troubleshoot during live node activities.

What you will bring

Expertise in DevOps pipeline orchestration and automation. Experience with any public cloud platforms: Azure, AWS, GCP. Must have: Git, Ansible, Python, Bash scripting, JSON/YAML, Ubuntu 20.04/22.04 and RHEL 7/8. Also valued: Kubernetes, GitLab, Docker, Azure DevOps, GitHub, Puppet/Chef, Cloudflare Access, Sonar. Qube (SAST), Artifactory.

Knowledge and hands-on experience in Git. Ops through Flux. Experience with common development tools: source code management, configuration management, security and compliance, artifact repositories and monitoring tools. Project management skills; Scrum, Agile and DevOps ways of working (preferred). AI/ML architecture: Proven experience designing large-scale AI/ML solutions for production and enterprise environments.

Programming and ML: Strong Python with hands-on Py. Torch and Tensor. Flow experience and modern deep-learning practices. GenAI and LLMs: Deep understanding of LLM architectures, fine-tuning, prompt engineering, inference optimization and enterprise deployment. RAG and knowledge systems: Hands-on experience with RAG pipelines, embeddings, vector databases, semantic search and knowledge-grounded AI applications.

Agentic AI: Familiarity with agentic AI frameworks, AI agents, tool calling, orchestration and integration protocols such as MCP. MLOps: Solid grasp of CI/CD, model lifecycle management, observability, governance, monitoring, retraining and continuous improvement. Enterprise architecture: Ability to translate complex business requirements into scalable, secure, resilient and cost-effective AI architectures.

You will also Design scalable, robust systems with development teams using cloud-native architectural principles. Build automation with industry-standard tools to deploy hundreds of services. Develop, manage and maintain automation assets of the Service Delivery Global DevOps Platform, including automation for platform infrastructure, applications and services.

Provide primary operational support, lifecycle management and engineering for platform systems and services. “All academic credentials must be from recognized and accredited institutions and are further subject to verification.”