Second Talent
Sr Engineer (Backend)
Mid-to-senior API Platform Engineer in Singapore building and scaling Menlo's API platform: designing APIs/SDKs, deploying AI/ML models to production, and running cloud-native infrastructure. Core stack: Python/TypeScript, Kubernetes/Docker/Helm, AWS/GCP/Azure, PostgreSQL/Redis, vector DBs, and observability tooling.
- Compensation
- Not disclosed
- Location
- Singapore
- Work setup
- Not specified
- Seniority
- Senior
- Employment
- Not specified
- Experience
- 3+ years
- Category
- Backend
- Posted
Skills
Must have
- 3+ years building and operating large-scale production systems with real-world usage and uptime expectations
- Containerization and orchestration: Kubernetes, Docker, Helm, service mesh (Istio or Linkerd)
- Cloud platforms (AWS, GCP, or Azure) including IAM, networking, and serverless tooling
- Hands-on coding in Python and JavaScript/TypeScript with backend frameworks (e.g., FastAPI, Express)
- Deep knowledge of API architecture: WebRTC/WebSockets, REST, gRPC, OpenAPI/Swagger, OAuth2/API keys, versioning
- Databases: PostgreSQL, Redis, modern vector databases (Pinecone, Weaviate, FAISS)
- CI/CD pipelines, GitOps, and tools like GitHub Actions, Argo CD, or Jenkins
- Monitoring and observability tools such as Prometheus, Grafana, Datadog, or OpenTelemetry
Nice to have
- MLOps tools and AI workflows: model versioning, inference pipelines, model registries
- Access control systems: ACLs, RBAC, multi-tenant security and isolation
- Billing systems, rate limiting, chargeback models, quota enforcement, usage metering
- Prior experience on developer platforms or API products with focus on UX and documentation
Full description
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)