Software Engineer - Infrastructure

Emergent Labs • San Francisco, CA

20h • Remote

About The Position

Emergent builds autonomous coding agents that replace traditional software development by generating, testing, and deploying production applications directly from plain-language intent. Their systems run in production at global scale and are used to build millions of real applications. Since public launch, Emergent has reached $100M ARR in 8 months, with over 6 million users across 190+ countries building more than 6.5 million applications. They have raised over $100M, backed by prominent investors including Khosla Ventures, SoftBank, Google, Lightspeed, Prosus, Together, and Y Combinator. The company focuses on solving the complex challenges of AI-driven software creation, specifically correctness, reliability, security, and scale in real production systems. The team comprises repeat founders, Olympiad medalists, IIT & IIM alumni, and leaders from major tech companies like Google, Amazon, and Dropbox. Emergent is seeking builders who desire ownership, speed, and significant impact at a global scale.

Requirements

• 4+ years of software/platform engineering experience with production systems
• Strong proficiency in Go or Python — you write production code in at least one daily
• Hands-on experience building and deploying services on Kubernetes — not just YAML, you've developed something that runs on K8s
• Experience with GitOps tooling (ArgoCD, Flux, or similar)
• Strong networking and DNS fundamentals — TCP/IP, HTTP, load balancing, DNS resolution, TLS, and debugging connectivity issues
• Solid Linux/OS fundamentals — process management, filesystem, memory, systemd, and comfortable debugging with tools like strace, tcpdump, and netstat
• Relational databases — experience with PostgreSQL, MySQL, or similar; indexing, query optimization, replication, and backup/restore procedures
• NoSQL databases — familiarity with MongoDB, DynamoDB, Redis, or similar for document/key-value workloads
• Caching — experience with Redis, Memcached, or similar for application and infrastructure-level caching
• Message queues & streaming — hands-on with Kafka, SQS, RabbitMQ, or similar for event-driven architectures
• Strong SQL skills for debugging and operational queries
• Comfortable with the CNCF ecosystem — Helm, Kustomize, cert-manager, Ingress controllers, CNI/CSI interfaces
• Hands-on with at least one observability stack (Grafana/Prometheus/Loki, New Relic, Datadog, or similar)
• Familiarity with GCP and/or AWS — managed Kubernetes (GKE/EKS), networking, IAM, storage, and cloud-native services (SES, SQS, S3, etc.)
• Experience with CDN/edge platforms (Cloudflare, CloudFront, or similar)

Nice To Haves

• Experience building Kubernetes Operators (kubebuilder, operator-sdk, or controller-runtime)
• Experience tuning Kubernetes core components (API server, kubelet, scheduler)
• Familiarity with AI/LLM infrastructure — token management, cost tracking, agent orchestration
• Experience with CI/CD pipelines (GitHub Actions, automated testing, deployment pipelines)
• Infrastructure as Code experience (Terraform, Pulumi, or similar)
• Previous work on large-scale distributed systems or platform-as-a-service
• Startup experience — you thrive in fast-paced, ambiguous environments

Responsibilities

• Maintain stability of our platform consisting of distributed microservices closely interacting with Kubernetes and cloud providers (GCP, AWS)
• Manage Kubernetes workloads with ArgoCD (GitOps) — deploy, monitor, and troubleshoot application syncs, resource trees, and rollouts
• Debug and resolve complex Kubernetes issues across clusters
• Manage CDN and edge infrastructure (Cloudflare) for performance, caching, and traffic management
• Automate infrastructure lifecycle operations and workflows
• Own the observability stack: Grafana (dashboards, Loki logs, Prometheus metrics), New Relic (APM, golden metrics, transaction analysis)
• Enhance monitoring, alerting, and distributed tracing across services
• Participate in on-call rotation via PagerDuty, handle incident response, and perform root cause analysis
• Proactively identify reliability risks before they become incidents
• Support the platform that runs AI agent workloads — job scheduling, trajectory tracking, environment provisioning, deployments and cost attribution
• Develop Kubernetes controllers and operators to extend platform capabilities for agent orchestration
• Work closely with product and backend teams to ensure platform scalability and reliability
• Build internal tools, automate workflows, and integrate systems to improve team productivity
• Stay current with Kubernetes releases, CNCF ecosystem updates, and cloud-native best practices

Benefits

• 401(k)
• Health, dental, and vision insurance
• Unlimited Paid Time Off: take the time you need to recharge and come back refreshed
• Flexible Working Hours: work arrangements that fit your life and commitments

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: No Education Listed