Cloud Native AI Engineer - Mid / Senior
Tasks
- Coordinate multidisciplinary technical teams
- Design AI ML pipelines from experimentation to production
- Implement MLOps LLMOps and DevSecOps processes
- Lead project design and technical mentoring
- Monitor AI models in production
- Serve as technical lead for enterprise AI architectures on Kubernetes
Perks/Benefits
- Company welfare program
- Electronic meal tickets
- Friend referral program
- Paid training
- Recharging Friday
Skills/Tech-stack
AI Agents | AWS | Agentic RAG | Agile | Ansible | Anthropic Claude | Apache Spark | Argo Rollouts | Argo Workflows | ArgoCD | Azure | Azure ML | BentoML | CI/CD | Cloud platform | DAST | Deep learning | DevSecOps | Elastic Stack | Feature Store | Flagger | Flink | Flux | GitHub Actions | GitLab CI | GitOps | Go | Google Cloud | Google Cloud Platform | Grafana | Graph Databases | Huggingface | ITIL | KServe | Kafka | Kubeflow | Kubernetes | Kubernetes Administration | Kubernetes security | LLMOps | Langchain | Langgraph | Llamaindex | Loki | MCP | MLOps | MLflow | Machine Learning | Meta LLAMA | Mistral | Model Context Protocol | Neo4j | Ollama | OpenAI | OpenShift AI | Operator pattern | Prince2 | Prometheus | Python | RAG | Ray Serve | Red Hat | Red Hat OpenShift | Red Hat OpenShift AI | SAST | SageMaker | Snyk | SonarQube | Terraform | Trivy | VLLM | Vector Databases | Vertex AI
Education
N/A
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