2 days ago
Singapore, SingaporeSenior
Responsibilities
- Design and develop production MCP Gateway and AI Gateway services for applications, AI agents, and LLM providers.
- Implement protocol-level functionality including MCP server and client support, request routing, streaming, tool-call proxying, authentication, authorization, and tenant isolation.
- Build high-throughput, low-latency network services involving TCP, TLS, HTTP, JSON streaming, connection pooling, and backpressure.
- Own application-side PostgreSQL schema design, indexing, query optimization, transactions, isolation levels, connection management, migrations, and performance.
- Design concurrent systems using worker pools, queues, graceful shutdown, backpressure, and race-free shared state.
- Profile services under load and resolve bottlenecks involving allocations, garbage collection, lock contention, and database performance.
- Build observability for AI systems covering metrics, tracing, logging, token usage, provider latency, cache hit rates, failure modes, and cost per request.
- Deploy, monitor, debug, and continuously improve reliable distributed services.
- Integrate directly with OpenAI-compatible and Anthropic APIs and evaluate, audit, and verify LLM outputs.
Requirements
- At least 5 years of senior-level experience in Go, Ruby, or both, including shipping and operating production services.
- For Go, deep standard-library knowledge, including net/http, crypto/tls, context, goroutines, channels, memory management, networking, and performance optimization.
- For Ruby, strong production Rails experience, including Ruby fundamentals and ActiveRecord tuning.
- Deep PostgreSQL knowledge from an application developer perspective, including query optimization, indexing, transactions, connection pooling, and large-scale migrations.
- Practiced concurrency and profiling experience, including debugging production incidents with a profiler.
- Familiarity with Kubernetes and containers, including resource limits, health checks, rolling deployments, and networking basics.
- Experience building production services with observability, deployment pipelines, security, and distributed-systems debugging.
- Experience with LLMs at the protocol level, including message structures, tool calling, streaming responses, and caching strategies.
- Familiarity with MCP and experience building or integrating MCP servers or clients is preferred.
- Ability to integrate with OpenAI-compatible and Anthropic APIs, evaluate responses, understand token usage, and optimize latency and cost.
- Ability to audit and verify LLM output, identify subtle bugs, security issues, and hallucinated APIs, and explain the underlying systems.
- Ability to participate in technical design and code reviews, communicate complex concepts clearly, and own the full service lifecycle.
Benefits
- Flexible, trust-oriented culture with ownership and a focus on innovation and teamwork.
- Benefits and a dynamic work environment supporting employees inside and outside of work.
- Access to major AI coding tools, IDEs, and frontier models with generous usage limits.
- Remote-friendly culture and tooling support for AI-assisted development.
Tech Stack
Categories
About Workato
Workato builds a cloud platform for enterprise integration and workflow automation, combining iPaaS, no-code recipes, and AI to orchestrate processes across SaaS and on‑prem systems. It sells subscriptions to IT and operations teams at large and mid-size companies; customers include firms such as Nasdaq, Cisco, and Atlassian. Founded in 2013 and headquartered in Palo Alto, it is a privately held company.