AI Infrastructure Engineer
Description
AI Infrastructure Engineer (Cloud-Native AI Platform | AWS/Terraform) South San Francisco, CA (3 days/week onsite preferred) - Remote possible (West Coast Time-Zone) | 6-month initial contract (potential long-term) Pay: $80–$90/hour, based on experience Overview Help build and scale the cloud infrastructure that powers our client’s AI enablement. As an AI Infrastructure Engineer , you’ll design, automate, and deploy cloud-native AI platform services —from infrastructure-as-code with Terraform/AWS CloudFormation to production-ready capabilities like workflow orchestration, messaging, artifact storage, vector search, and secure execution . If you enjoy turning AI and agentic application requirements into reliable platforms that teams can build on, this role is for you. Required Skills Strong communication, collaboration, and interpersonal skills Experience implementing CI/CD pipelines and deployment automation using CI/CD tools Infrastructure-as-Code (IaC) experience using Terraform and/or AWS CloudFormation Deep experience with Amazon Web Services, including (as applicable): IAM, VPC, API Gateway, NLB, ALB, EC2, ECS, EKS, Lambda, S3, RDS Experience with Kubernetes, Helm, and Docker containerization Proficiency in Python and Bash scripting Understanding of networking and protocols including HTTP, DNS, TLS, TCP Ability to design and build frameworks/services such as Python SDKs and REST or gRPC APIs Experience with distributed systems and event-driven architectures, including messaging systems or workflow orchestration platforms Nice to Have Skills Familiarity with vector databases/search (e.g., MongoDB Atlas, pgvector, Pinecone, Weaviate) Experience with AI/LLM APIs and model platforms (e.g., OpenAI, Gemini, Anthropic) Familiarity with common agent frameworks/patterns (e.g., LangGraph, CrewAI, LlamaIndex, ReAct) Experience with observability/monitoring tools (e.g., Prometheus, Grafana, LangSmith, Langfuse) Familiarity with AI/ML platform engineering, MLOps, or AgentOps concepts Preferred Education And Experience Preferred: Bachelor’s degree in Computer Science, Engineering, or related field (or equivalent practical experience) Preferred experience level: Candidates with hands-on experience building and operating cloud infrastructure and platform services for production systems (AI/ML platform engineering experience is a plus) Other Requirements Hybrid Onsite Preference: South San Francisco, CA 3 days/week onsite - if remote is required, should be West Coast timezone Term: 6-month initial contract (could be long term) W2/1099 candidates are welcome If you’re excited to build reliable, automated AI infrastructure on AWS—apply now and let’s connect your experience to the platform our client is scaling. Show more Show less