Senior Software Engineer; Go/Ruby Gateways & Enterprise AI Infrastructure
Singapore
Listed on 2026-09-02
-
Software Development
Backend Developer, AI Engineer (Applied/Software), Software Engineer
About Workato
Workato delivers enterprise infrastructure for the agentic era, redefining iPaaS and helping enterprises unify data, applications, processes, and AI into a single, governed platform. A leader in Enterprise MCP and trusted by 50% of the Fortune 500, Workato’s cloud-native architecture connects every application, data source, and process to power real-time orchestration h enterprise-grade security and continuous innovation at its core, Workato provides the trusted foundation for organizations to automate with confidence and operationalize AI across the business.
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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
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 Software Engineer (Go/Ruby) – Gateways & Enterprise AI Infrastructure 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, you 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.
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 unexplored.
We actively explore and enhance automated development. You’ll help shape how the team uses AI: agent workflows, code review automation, internal tooling. We build AI infrastructure, so we hold ourselves to being its most sophisticated users.
We believe LLM tools give a single engineer full visibility across the product
, regardless of area — frontend, backend, infra,…
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