Sr Engineer (Backend)
TypeFull-time job
LocationSingapore
Posted3 hours ago
We are looking for a mid to senior level API Platform Engineer.
In this role, youll architect and scale the foundation that powers delightful developer experiences and production-grade AI systems. You'll work at the intersection of high-performance APIs, scalable infrastructure, and cutting-edge machine learningdelivering tools that enable developers and partners to build on top of Menlos intelligent platform.
Responsibilities
Design and build the Menlo API Platform, focusing on high reliability, performance, and a world-class developer experience
Develop intuitive APIs and SDKs that make it easy for developers to access and integrate multimodal AI capabilities
Deploy and optimize AI/ML models into scalable, production environments, working closely with research and applied ML teams
Manage and evolve a modern, cloud-native infrastructure stack, using Kubernetes, Docker, and infrastructure-as-code (IaC) tools
Ensure platform reliability, including designing and implementing telemetry, monitoring, alerting, autoscaling, failover, and disaster recovery mechanisms
Contribute to developer and operations workflows, including CI/CD pipelines, release management, and on-call rotations
Collaborate across teams to implement secure APIs with fine-grained access control, usage metering, and billing integration
Continuously improve platform performance, cost-efficiency, and observability as we scale to serve millions of users worldwide
Requirements
3+ years of experience building and operating large-scale, production systems with real-world usage and uptime expectations
Strong experience with containerization and orchestration: Kubernetes, Docker, Helm, and service mesh technologies (e.g., Istio or Linkerd)
Proficiency with cloud platforms: AWS, GCP, or Azure including experience with IAM, networking, and serverless tooling
Hands-on coding skills in Python and JavaScript/TypeScript, with familiarity in backend frameworks (e.g., FastAPI, Express)
Deep knowledge of API architecture and design patterns: WebRTC/Websockets, REST, gRPC, OpenAPI/Swagger, authentication (OAuth2, API keys), and versioning
Experience with databases: PostgreSQL, Redis, and modern vector databases (e.g., Pinecone, Weaviate, FAISS)
Familiarity with CI/CD pipelines, GitOps practices, and tools like GitHub Actions, Argo CD, or Jenkins
Comfortable with monitoring and observability tools such as Prometheus, Grafana, Datadog, or OpenTelemetry
Bonus Experience
Experience with MLOps tools and AI workflows: model versioning, inference pipelines, model registries, etc.
Understanding of access control systems: ACLs, RBAC, multi-tenant security and isolation
Knowledge of billing systems, rate limiting, chargeback models, quota enforcement, and usage metering
Prior experience working on developer platforms or API products with a strong focus on UX and documentation
Originally posted on Himalayas
In this role, youll architect and scale the foundation that powers delightful developer experiences and production-grade AI systems. You'll work at the intersection of high-performance APIs, scalable infrastructure, and cutting-edge machine learningdelivering tools that enable developers and partners to build on top of Menlos intelligent platform.
Responsibilities
Design and build the Menlo API Platform, focusing on high reliability, performance, and a world-class developer experience
Develop intuitive APIs and SDKs that make it easy for developers to access and integrate multimodal AI capabilities
Deploy and optimize AI/ML models into scalable, production environments, working closely with research and applied ML teams
Manage and evolve a modern, cloud-native infrastructure stack, using Kubernetes, Docker, and infrastructure-as-code (IaC) tools
Ensure platform reliability, including designing and implementing telemetry, monitoring, alerting, autoscaling, failover, and disaster recovery mechanisms
Contribute to developer and operations workflows, including CI/CD pipelines, release management, and on-call rotations
Collaborate across teams to implement secure APIs with fine-grained access control, usage metering, and billing integration
Continuously improve platform performance, cost-efficiency, and observability as we scale to serve millions of users worldwide
Requirements
3+ years of experience building and operating large-scale, production systems with real-world usage and uptime expectations
Strong experience with containerization and orchestration: Kubernetes, Docker, Helm, and service mesh technologies (e.g., Istio or Linkerd)
Proficiency with cloud platforms: AWS, GCP, or Azure including experience with IAM, networking, and serverless tooling
Hands-on coding skills in Python and JavaScript/TypeScript, with familiarity in backend frameworks (e.g., FastAPI, Express)
Deep knowledge of API architecture and design patterns: WebRTC/Websockets, REST, gRPC, OpenAPI/Swagger, authentication (OAuth2, API keys), and versioning
Experience with databases: PostgreSQL, Redis, and modern vector databases (e.g., Pinecone, Weaviate, FAISS)
Familiarity with CI/CD pipelines, GitOps practices, and tools like GitHub Actions, Argo CD, or Jenkins
Comfortable with monitoring and observability tools such as Prometheus, Grafana, Datadog, or OpenTelemetry
Bonus Experience
Experience with MLOps tools and AI workflows: model versioning, inference pipelines, model registries, etc.
Understanding of access control systems: ACLs, RBAC, multi-tenant security and isolation
Knowledge of billing systems, rate limiting, chargeback models, quota enforcement, and usage metering
Prior experience working on developer platforms or API products with a strong focus on UX and documentation
Originally posted on Himalayas
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