Platform Engineer - AI Agent Infrastructure

This is a high-impact engineering opportunity to shape the infrastructure behind a rapidly growing AI agent platform operating at global scale. You will take ownership of core cloud architecture, ensuring systems remain reliable, observable, and ready for continuous expansion. The role combines deep infrastructure expertise with strong architectural thinking, making it ideal for someone who enjoys building scalable distributed systems rather than simply maintaining existing environments. You will lead decisions around messaging systems, automation, deployment pipelines, and platform resilience. Working in a remote and innovation-driven environment, you will collaborate with high-performing teams using modern cloud and AI technologies. This is an opportunity to directly influence the future of AI infrastructure in production environments. Accountabilities:

• Own and evolve the cloud infrastructure supporting AI agents running at scale in production environments
• Design and implement event-driven architectures using durable asynchronous messaging systems
• Improve inter-service communication by replacing synchronous dependencies with scalable messaging patterns
• Build and maintain infrastructure as code frameworks for provisioning, deployment, and environment consistency
• Ensure platform reliability, scalability, and performance across distributed workloads
• Develop advanced observability capabilities including dashboards, alerts, tracing, logging, and health monitoring
• Lead incident response analysis and proactively improve system resilience based on production learnings
• Evaluate emerging technologies and drive architectural decisions as the platform matures
• Optimize databases, storage systems, and caching layers for speed, availability, and cost efficiency
• Collaborate with engineering teams to support secure and efficient deployment of AI workloads

• 4+ years of experience in platform engineering, infrastructure engineering, SRE, or backend systems roles
• Strong expertise in event-driven architecture and messaging systems such as Kafka, RabbitMQ, NATS, or similar
• Deep AWS experience including EC2, VPC, IAM, S3, RDS, and internal networking concepts
• Solid experience with SQL databases such as PostgreSQL and NoSQL systems such as MongoDB or Redis
• Strong Docker knowledge including container lifecycle management, health checks, resource limits, and image optimization
• Proven experience debugging distributed systems, asynchronous flows, and cascading production failures
• Hands-on experience with Infrastructure as Code tools such as Terraform or Pulumi
• Strong observability skills using Datadog or equivalent tools for APM, logging, monitoring, and tracing
• Experience with Go or similar backend programming languages
• Strong communication skills and ability to lead technical decisions in remote teams, * Experience supporting AI or MLOps infrastructure, model serving, LLM inference, or GPU workloads
• Familiarity with LangFuse, LangSmith, Braintrust, MLflow, or similar AI observability tools
• Experience building multi-tenant container platforms or internal PaaS environments
• Kubernetes migration or production operations experience
• Exposure to Airflow, Prefect, Snowflake, BigQuery, Databricks, or similar data platforms
• ECS and AI agent framework ecosystem knowledge is a plus

• Competitive compensation package
• Fully remote work from anywhere
• One-time home office setup allowance
• Company-provided work equipment
• Stock options
• Health plan coverage regardless of location
• Flexible paid time off
• Language learning and professional development courses
• Personal growth and continuous learning support
• Opportunity to shape cutting-edge AI infrastructure at scale