Location: Singapore ONLY. No relocation package available.

Format: Hybrid (office in Suntec City).

Employment: Full-Time.

About the Company/Product:

• A global B2B product company developing a powerful Integration Platform as a Service (iPaaS) that uses AI and machine learning to enable organizations to seamlessly connect data sources, cloud applications, and enterprise systems through low-code/no-code automation.
• The platform is trusted by more than 400,000 customers worldwide, including leading companies such as Visa, Goldman Sachs, Cisco, Amazon, HubSpot, and L’Oréal.
• The engineering culture emphasizes technical excellence, strong ownership, and close collaboration across globally distributed teams.

About the Role:

We are looking for several Senior Go/Ruby Engineers to join our Gateways team, which builds the platform's core gateway infrastructure across several directions: the Model Context Protocol (MCP) Gateway, AI Gateway, and API Management (APIm).

You will work across both MCP and AI Gateways, which overlap closely. These are the systems that sit between applications, AI agents, and model providers. Here are some of the exciting things you might contribute to:

• Building and evolving the core services of both gateways, not applications sitting on top of them.
• Handling the protocol side: dispatching model and tool calls, authentication and tenant isolation in a multi-tenant setup, and long-lived streaming sessions held open across real networks and load balancers.
• Keeping throughput and tail latency predictable — connection management, backpressure, concurrent processing — and when they slip, profiling the running service and fixing the actual cause.
• Designing the observability for everything you ship, including the AI-specific signals: latency per provider, tokens consumed, cache hit rates, cost per request.
• Working with PostgreSQL in depth: schemas, indexes, and queries that hold up as volume grows.
• Shipping into a live product that keeps moving: parts get redesigned and rewritten in flight, and each engineer carries their slice from design through production and keeps it afterwards.
• Shaping how the team works with AI tooling: agent-driven workflows, automated code review, internal utilities.
• Collaborating with the Infra/SRE teams on availability and scaling; architecture and code reviews.

Core Tech Stack: Golang, Ruby on Rails, Kubernetes, PostgreSQL, modern AI tooling.

What You Have: