Senior AI Engineer Job Singapore,Software Development

About Workato

Workato is the leading Control and Execution Platform for Enterprise AI — the neutral platform enterprises trust to put AI to work across their business. Workato unifies data, applications, and processes into a single platform so AI can reliably orchestrate business processes in production at enterprise scale. Built on more than a decade of running mission-critical processes for over half the Fortune 500 — including Nasdaq, Amazon, Cisco, Vodafone, Atlassian, and Lucid Motors — Workato turns over 14,000 enterprise systems AI needs to act on into one governed execution layer.

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Why join us?

Ultimately, Workato believes in fostering a flexible, trust-oriented culture that empowers everyone to take full ownership of their roles
. We are driven by innovation and looking for team players who want to actively build our company.

But, we also believe in balancing productivity with self-care
. That’s why we offer all of our employees a vibrant and dynamic work environment along with a multitude of benefits they can enjoy inside and outside of their work lives.

Also, feel free to check out why:

Business Insider named us an “enterprise startup to bet your career on”
Forbes’ Cloud 100 recognized us as one of the top 100 private cloud companies in the world
Deloitte Tech Fast 500 ranked us as the 17th fastest growing tech company in the Bay Area, and 96th in North America
Quartz ranked us the #1 best company for remote workers

Responsibilities

We're building the infrastructure layer that connects enterprise systems to AI: an MCP Gateway
, an AI Gateway
, and the services around them. These are the systems that sit between LLM providers and everything else — routing, auth, rate limiting, observability, protocol translation. We're looking for a senior engineer who understands both the systems layer and the AI protocol layer, and who can build production-grade services in Go and/or Ruby.

In this role, y ou will also be responsible to:

Design and develop the MCP Gateway and AI Gateway — production services that mediate between applications, AI agents, and LLM providers. This means protocol-level work: MCP server/client implementations, request routing, streaming, tool-call proxying, authn/authz, and tenant isolation. You'll build the core infrastructure, not just applications on top of it.
Build high-throughput, low-latency network services. You'll work close to the wire: TCP, TLS, HTTP/1.1 and HTTP/2, JSON streaming, connection pooling, back pressure. When latency matters, you'll know exactly where it goes.
Own the data layer from the application side. Deep PostgreSQL knowledge — schema design, indexing strategies, query planning, transactions and isolation levels, connection management. You're not a DBA, but you can read EXPLAIN ANALYZE output and fix the query, not just add an index and hope.
Design for concurrency. Worker pools, queues, graceful shutdown, back pressure, race-free shared state. You can profile a service under load (pprof, flame graphs, query stats), find the bottleneck, and fix it.
Drive observability for AI systems. Metrics, tracing, and logging that actually tell you what's happening — token usage, latency per provider, cache hit rates, failure modes, cost per request.

How we work with AI

We encourage — but never force — the use of AI/LLM tools in development. If AI-assisted workflows make you faster, use them heavily. If you prefer to write something by hand, that's equally respected. What we care about is the quality of what ships, not how it was typed.
You'll have access to nearly every major tool and model on the market — coding agents, IDEs, frontier models — with very generous usage limits. We want tooling budget to never be the reason a good idea goes…