We are seeking a highly skilled AWS AI Engineer with strong hands-on experience in Kubernetes, EKS, and Generative AI systems. The ideal candidate will have deep expertise in deploying, scaling, and maintaining AI/ML workloads in production environments, along with experience in modern AI frameworks and platform engineering.
Certification Requirements (At least one required)
Active AWS Solutions Architect Certification
AWS Certified AI Foundations or AWS Certified AI Professional
Certified Kubernetes Administrator (CKA) - Active certification
Key Responsibilities
Deploy, manage, and troubleshoot Kubernetes clusters, including disconnected installations
Design, deploy, and upgrade Amazon EKS clusters in production environments
Perform advanced troubleshooting for EKS and Kubernetes-based systems
Implement and manage LLMOps workflows, including deployment, monitoring, and scaling of Generative AI systems
Build and maintain agent-based workflows using frameworks like LangChain, CrewAI, or AutoGen
Manage and optimize vector databases (e.g., Pinecone, Weaviate, Milvus)
Design and optimize Retrieval-Augmented Generation (RAG) pipelines for performance and scalability
Implement AI governance frameworks, including security guardrails and cost optimization strategies
Build and support Internal Developer Platforms (IDP) for AI use cases
Must-Have Skills
Strong Kubernetes expertise (installation, administration, troubleshooting)
Extensive hands-on experience with Amazon EKS (deployment, upgrades, troubleshooting)
Proven experience with LLMOps and production-grade Generative AI systems
Experience with agentic AI frameworks (LangChain, CrewAI, AutoGen)
Hands-on experience with vector databases and RAG architectures
Knowledge of AI governance, security guardrails (e.g., NeMo Guardrails), and cost control for LLMs
Experience building AI-focused Internal Developer Platforms