Lead DevOps Engineer

Lead DevOps Engineer (Remote - US)

Location: Remote in the United States
Type: Full-time
Focus: AWS cloud infrastructure for AI-native real estate initiatives

Role Overview

As a Lead DevOps Engineer, you will design, architect, deploy, and maintain foundational cloud infrastructure that powers AI-native platforms. You’ll collaborate closely with AI/ML, development, product, and leadership teams, applying a DevOps mindset to build scalable, reliable, and secure systems.

You’ll be part of the Cloud Solutions team supporting internally developed applications across AWS, GCP, and Azure, with this role focusing specifically on AWS.

Responsibilities

• Own DevOps/cloud platform capabilities end-to-end for production platforms
• Architect and operate AWS infrastructure for AI-native platform workloads
• Build and maintain serverless and container-based systems
• Implement Infrastructure-as-Code with modular patterns and remote state backends
• Deliver and maintain CI/CD pipelines using GitHub Actions
• Apply security best practices (least-privilege IAM, secrets handling, WAF, isolation patterns)
• Support platform observability and operations with monitoring/logging

Requirements

• 9+ years in DevOps, cloud platform engineering, or SRE
• 2+ years owning a production platform end-to-end
• Strong Python skills (debugging and writing code; FastAPI/Lambda experience)
• Deep production experience with AWS ECS/Fargate
• Strong serverless AWS expertise:
  • Lambda, API Gateway, Step Functions, EventBridge, SQS/SNS, SES
• Strong knowledge of core AWS services, including:
  • VPC (private subnets, NAT, VPC endpoints), IAM, S3, Secrets Manager
  • CloudWatch, ALB, CloudFront, WAF, Route53, ACM
  • RDS/Aurora
• Infrastructure-as-Code with OpenTofu or Terraform, including modular design and remote backends (e.g., Scalr/HCP/TFC)
• CI/CD using GitHub Actions
• Container engineering experience (e.g., Docker image design, multi-arch builds, image hardening, layer caching)
• Security expertise including least-privilege IAM, OIDC, WAF rule design, secret handling, and sandbox isolation patterns

Nice to Have

• Operating agentic AI/LLM workloads in production (e.g., Bedrock, Langfuse, LangGraph/LangChain, MCP servers, cost tracking)
• Experience with Snowflake Cortex or similar warehouse-native AI features
• DevOps-adjacent experience (software engineering, ML, Data Science)
• Multi-cloud experience (GCP, Azure)

Compensation

Salary range stated: $180k - $200k+ (final offer depends on factors including experience, location, responsibilities, and certifications).