Forward Deployed Engineer, Japan

• Troubleshoot and resolve complex integration issues alongside customer teams

What We're Looking For

• CS degree or equivalent experience
• 3+ years building and shipping production software — you've written code that real users depended on, you've been on-call for it, and you've debugged it when things broke. (A consulting background counts if this is also true of you.)
• Proficiency in multiple languages: Python, Node.js/TypeScript, Go — you're more dangerous in some than others. (Telnyx Edge Compute — functions and stateful actors — is TypeScript, so that one pulls double duty.)
• Practical understanding of what breaks in front of a model in production: provider rate limits and quotas, timeout and retry behavior, streaming, token accounting and cost attribution, and the failure modes that only show up under concurrency
• Comfortable deploying containerized services on Kubernetes, with secrets management, config, and upgrades as part of the deployment story
• You've wired observability and been paged because of it — Prometheus + Grafana, OpenTelemetry, Graylog, ELK, or equivalent. You know what to monitor, what to alert on, and what "healthy" looks like
• High-concurrency experience — Kafka, message queues, or event streams at real scale. When throughput spikes you know what breaks — consumer lag, backpressure, hot partitions, rebalance stalls — and what absorbs it: partitioning, consumer groups, parallelism up to your partition count
• You've built APIs from scratch, not just consumed them — OpenAPI spec, REST/GraphQL design, auth, rate limiting, versioning, idempotency
• Event-driven thinking and cloud-native instincts
• Exposure to SIP, WebRTC, or real-time voice/messaging systems
• Self-sufficient by default — there's no engineering team behind you. You read the code and the docs, ask the customer (not your manager), and make sound engineering judgment calls on your own
• Customer-facing engineering experience — you can run discovery with a customer's engineers and present to their executives in the same week
• Ability to translate "it's not working" into root cause
• Comfortable working on customer sites and in high-stakes technical conversations
• Excellent written and verbal communication in English [and Japanese]. You can run whiteboard sessions, live troubleshooting, and escalations with customer engineering teams.
• Based in Tokyo, or willing to relocate — this is a hybrid role with travel across Japan and the broader APAC region
• Legally authorized to work in Japan, or eligible for sponsorship

Bonus Points For

• Experience with AI voice assistants, STT/TTS, or LLM-based conversational systems
• Building eval sets for a specific domain
• Hands-on production experience with an LLM gateway — LiteLLM, Portkey, Kong AI Gateway, or an in-house OpenAI-compatible proxy — including config-driven model definitions, routing and fallback rules, and virtual key management
• Familiarity with the open-weight model landscape and the trade-offs between regional and multilingual models, including Japanese-language models (Swallow, PLaMo, ELYZA, Rinna) and Japanese sovereign AI initiatives
• Experience with an inference serving engine behind the gateway — vLLM, SGLang, or TGI for production serving; Ollama for lightweight on-prem — and sizing GPU capacity for self-hosted models (KV-cache footprint, concurrent batch size, and context length against VRAM)
• SQL proficiency (Postgres, MySQL, Oracle)
• ETL and data wrangling experience
• CI/CD pipeline design and automation
• Background in telecom, CPaaS, or high-growth SaaS
• Experience with sovereign or on-prem cloud deployments and Japan/APAC regulatory frameworks (APPI, METI cloud security guidelines, FSA cloud outsourcing guidelines for financial services, Japan data localization considerations, APAC cross-border data transfer frameworks)
• Security mindset (IAM, encryption, audit logging)