Senior DevOps Engineer – Generative AI & Cloud Solutions
Core
Design, automate, and secure cloud infrastructure for hosting, fine-tuning, and serving Generative AI models and LLM applications.
Role type
Senior DevOps Engineer (Generative AI & LLMOps)
Builds
Scalable cloud environments, CI/CD pipelines, and deployment frameworks for Large Language Models (LLMs) and AI integrations.
Domain
Cloud Infrastructure & Generative AI
Deliverable
production ML models
Required skills
Kubernetes, Docker, Terraform, CI/CD pipeline management, vector databases, cloud architecture (AWS/Azure/GCP), GPU/TPU resource management, observability tools, LLM deployment frameworks (LangChain, LlamaIndex, Semantic Kernel), RAG pipeline optimization, cost optimization for heavy compute.
Preferred skills
Experience with OpenAI APIs, Hugging Face, Anthropic, or open-source models (Llama via Ollama/vLLM), familiarity with pgvector.
Technologies
AWS, Azure, GCP, Docker, Kubernetes, Terraform, OpenTofu, CloudFormation, GitHub Actions, GitLab CI, Jenkins, Prometheus, Grafana, Datadog, Pinecone, Milvus, Qdrant, PostgreSQL, LangChain, LlamaIndex, Semantic Kernel, Ollama, vLLM.
Responsibilities
Design and manage cloud infrastructure for hosting and serving Generative AI models; Implement and manage infrastructure for AI orchestration frameworks; Optimize vector databases for Retrieval-Augmented Generation (RAG) pipelines; Implement cost-optimization strategies for heavy compute resources; Architect, scale, and maintain secure, cloud-native infrastructure; Orchestrate and manage containerized workloads; Build, maintain, and optimize secure CI/CD pipelines; Set up advanced observability tools to track infrastructure health and AI model performance metrics; Collaborate with engineering teams to ensure secured IT solutions with data privacy and guardrails for LLM prompts/outputs.
Seniority
Senior, hands-on IC
