Software Engineer - Infrastructure

Emergent builds autonomous coding agents that replace traditional software development by generating, testing, and deploying production applications directly from plain-language intent. Our 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. 6M+ users across 190+ countries have built 6.5M+ applications on Emergent. We've raised $100M+, backed by Khosla Ventures, Soft Bank, Google, Lightspeed, Prosus, Together, and Y Combinator.

We're solving the hard part of AI-driven software creation: correctness, reliability, security, and scale in real production systems. The team is built by repeat founders, Olympiad medalists, IIT & IIM alumni, and leaders from Google, Amazon, and Dropbox.

We're hiring builders who want ownership, speed, and impact at global scale.

• Maintain stability of our platform consisting of distributed microservices closely interacting with Kubernetes and cloud providers (GCP, AWS)
• Manage Kubernetes workloads with ArgoCD (Git Ops) — 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 Pager Duty
  , 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

• 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 Git Ops 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, file system, memory, systemd, and comfortable debugging with tools like strace, tcpdump, and netstat

• Relational databases
  — experience with Postgre
  
  SQL, MySQL, or similar; indexing, query optimization, replication, and backup/restore procedures
• No
  
  SQL databases
  — familiarity with Mongo
  
  DB, Dynamo
  
  DB, 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, Rabbit
  
  MQ, 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, Cloud Front, or similar)

• Experience building Kubernetes Operators (kubebuilder, operator-sdk, or controller-runtime)
• Familiarity with AI/LLM…