2 days ago
Responsibilities
- Design and develop MCP Gateway and AI Gateway services for applications, AI agents, and LLM providers.
- Implement protocol-level capabilities including MCP servers and clients, request routing, streaming, tool-call proxying, authentication and authorization, and tenant isolation.
- Build high-throughput, low-latency services using networking, connection pooling, concurrency, worker pools, queues, and backpressure techniques.
- Design and optimize PostgreSQL schemas, indexes, queries, transactions, connection management, and migrations at scale.
- Profile services under load, diagnose bottlenecks, and improve performance, memory use, garbage collection, and lock contention.
- Build observability for AI systems covering metrics, tracing, logging, token usage, provider latency, cache hit rates, failures, and cost per request.
- Own the full lifecycle of services from design and implementation through deployment, monitoring, incident debugging, and continuous improvement.
- Participate in technical design discussions, code reviews, AI-assisted development workflows, and internal tooling improvements.
Requirements
- 5+ years of senior-level experience with Go, Ruby, or both, including shipping and operating production services.
- For Go, deep knowledge of the standard library, networking, concurrency, memory behavior, and real-service performance optimization.
- For Ruby, strong production Rails and Ruby experience, including ActiveRecord tuning and performance under load.
- Deep application-developer experience with PostgreSQL, including query optimization, indexing, transactions, connection pooling, and large-scale migrations.
- Practiced experience with concurrency, profiling, production incident debugging, observability, deployment pipelines, and distributed systems.
- Familiarity with Kubernetes and containers, including deployment, debugging, resource limits, health checks, rolling deployments, and networking basics.
- Experience working with LLMs at the protocol level, including message structures, tool calling, streaming responses, and caching strategies.
- Ability to integrate directly with OpenAI-compatible and Anthropic APIs, evaluate responses, understand token usage, and optimize latency and cost.
- Ability to audit and verify LLM output and identify subtle bugs, security issues, and hallucinated APIs.
- Familiarity with MCP, including MCP server or client integration, transport, and capability negotiation, is a strong plus.
- Strong communication, technical design, code review, learning, and end-to-end ownership skills.
Benefits
- Flexible, trust-oriented culture with strong role ownership and a dynamic work environment.
- Access to major AI coding tools, IDEs, and frontier models with generous usage limits.
- Role based in Singapore.
- Company offers a range of employee benefits, though specific benefits are not detailed in the posting.
Tech Stack
Categories
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. We connect to every app, system, and process your business runs on, with no data migration, no rip-and-replace, 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 14,000+ enterprise systems into one governed execution layer. AI has solved reasoning. The next frontier is execution, with Workato.