[Hiring] Senior AI Engineer @Workato

Role Description

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, 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.
• 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, backpressure.
• Own the data layer from the application side. Deep PostgreSQL knowledge — schema design, indexing strategies, query planning, transactions and isolation levels, connection management.
• Design for concurrency. Worker pools, queues, graceful shutdown, backpressure, race-free shared state.
• 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 actively explore and enhance automated development. You'll help shape how the team uses AI: agent workflows, code review automation, internal tooling.

We believe LLM tools give a single engineer full visibility across the product, regardless of area — frontend, backend, infra, docs.

But the accountability never shifts to the machine. You own what you merge. You can explain every statement and decision in the final output, and justify and defend the architectural choices to human colleagues in design and code reviews.

Qualifications

• Senior-level experience (5+ years) in Go, Ruby, or both.
• Deep PostgreSQL knowledge from an application developer's perspective.
• Concurrency and profiling as a practiced skill.
• Familiarity with Kubernetes and containers.
• AI/LLM experience at the protocol level.
• Familiarity with MCP (Model Context Protocol) is a strong plus.

Requirements

• Go candidates: deep knowledge of stdlib, performance optimization on real services, and understanding of networking.
• Ruby candidates: strong Rails in production and tuning ActiveRecord.
• Experience with query optimization, indexing, transactions, connection pooling, migrations at scale.
• Experience building production services with proper observability, deployment pipelines, and security.
• Ability to integrate with OpenAI-compatible and Anthropic APIs directly.
• Ability to judge, audit, and verify LLM output.

Benefits

• Flexible, trust-oriented culture that empowers ownership of roles.
• Vibrant and dynamic work environment.
• Multitude of benefits for employees to enjoy inside and outside of work lives.