AI Infrastructure Engineer

About the role

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.

Responsibilities

• Design, automate, and deploy cloud-native AI platform services
• Implement CI/CD pipelines and deployment automation using CI/CD tools
• Build and manage infrastructure-as-code (IaC) using Terraform and/or AWS CloudFormation
• Work with Amazon Web Services, including IAM, VPC, API Gateway, NLB, ALB, EC2, ECS, EKS, Lambda, S3, RDS
• Use Kubernetes, Helm, and Docker for containerization
• Write Python and Bash scripts for automation
• Design and build frameworks/services like Python SDKs and REST or gRPC APIs
• Work with distributed systems and event-driven architectures, including messaging systems or workflow orchestration platforms

Requirements

• Strong communication, collaboration, and interpersonal skills
• Experience implementing CI/CD pipelines and deployment automation
• Deep experience with Amazon Web Services, including IAM, VPC, API Gateway, NLB, ALB, EC2, ECS, EKS, Lambda, S3, RDS
• Experience with Kubernetes, Helm, and Docker
• Proficiency in Python and Bash scripting
• Understanding of networking and protocols including HTTP, DNS, TLS, TCP
• Experience with distributed systems and event-driven architectures, including messaging systems or workflow orchestration platforms

Qualifications

• 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)

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

Benefits

Hybrid Onsite Preference: South San Francisco, CA 3 days/week onsite - if remote is required, should be West Coast timezone

Pay

$80–$90/hour, based on experience

Schedule

6-month initial contract (could be long term)

Other Requirements

• W2/1099 candidates are welcome