Roles and Responsibilities :
Build and run COS as a secure cloud-native platform (containers, Kubernetes, OpenStack), using infrastructure/configuration as code.
Introduce AI-enabled operations (AIOps) and MLOps/LLMOps practices: automate detection/diagnosis, and set up protected, observable delivery and monitoring of AI components.
Execute deployments, upgrades, and configuration changes; troubleshoot by reproducing issues, restoring service, and running performance/load tests as needed.
Improve secure CI/CD for platform and services: testing, scanning, policy checks, controlled releases, and compliance (risk assessments, audits, configuration baselines).
Apply SRE practices to improve availability, scalability, and performance, and drive proactive monitoring and reliability improvements.
Take operational ownership with the team: runbooks, on-call readiness, incident/problem management, SLA follow-up, access management, and service performance reporting.
Tech stack spans cloud-native microservices (e.g., Go, Svelte, Kubernetes), telemetry backends (e.g., Cortex), and data systems (e.g., Postgres/Cassandra/Kafka).

Job Requirements :




6+ years in DevSecOps or platform engineering in a cloud-native environment, with end-to-end ownership across build and run.
Tech stack spans cloud-native microservices (e.g., Go, Svelte, Kubernetes), telemetry backends (e.g., Cortex), and data systems (e.g., Postgres/Cassandra/Kafka).
Robust CI/CD and automation skills, including security checks (SAST/SCA, image scanning, policy checks) and controlled releases.
Solid understanding of cloud-native observability (Grafana, Prometheus, Loki) and instrumentation with OpenTelemetry.
Comfortable working across a broad tech stack and learning current tools and concepts quickly.
Clear communicator who collaborates globally and can explain our work across development, operations, and security. You enjoy mentoring and sharing practices in the team/community.
Proactive problem-solver who thrives in hands-on engineering and structured delivery, and enjoys making production systems secure, predictable, and observable.
Merit: AI platform engineering (MLOps/LLMOps), deploying/monitoring LLM services, RAG pipelines, and embeddings/vector search. Ericsson experience is a plus.

📌 Devsecops Engineer Bengaluru
🏢 Ericsson
📍 Bengaluru