DevOps Architect
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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
- Demonstrable experience in full-stack systems and software development.
- Expertise in DevOps pipeline orchestration and automation.
- Experience with 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, SonarQube (SAST), Artifactory.
- Knowledge and hands-on experience in GitOps 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 PyTorch and TensorFlow 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.”
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