Sr Engineer (Backend)

Second Talent; Singapore; On-site; SGD 70,000 - 100,000; Full time

Job summary

A tech recruitment company in Singapore is looking for a mid to senior level API Platform Engineer. This role involves designing and building a robust API platform to enhance developer experiences and scaling AI systems. The ideal candidate will have over 3 years of experience with large-scale systems, strong skills in cloud platforms, and familiarity with Python and JavaScript frameworks. Experience with Kubernetes, Docker, and API design is crucial for this position, which offers opportunities to work on the latest technologies.

Qualifications

• 3+ years of experience in building and operating large-scale, production systems.
• Strong experience with Kubernetes, Docker, and service mesh technologies.
• Proficiency in Python and JavaScript/TypeScript with backend frameworks familiarity.

Responsibilities

• Design and build the Menlo API Platform for reliability and performance.
• Develop intuitive APIs and SDKs for multimodal AI capabilities.
• Manage a cloud-native infrastructure stack using Kubernetes and Docker.

Skills

Containerization and orchestration

Cloud platforms (AWS, GCP, Azure)

Python programming

JavaScript/TypeScript

API architecture and design patterns

Monitoring and observability tools

CI/CD pipelines

Tools

Kubernetes

Docker

PostgreSQL

Redis

Job description

We are looking for a mid to senior level API Platform Engineer.

In this role, you'll 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 learning delivering tools that enable developers and partners to build on top of Menlo's 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