Forward Deployed Engineer（フォワードデプロイドエンジニア） ／ ソリューションエンジニア・カスタマーエンジニア

About the Position

About Telnyx

Telnyx is an industry leader that's not just imagining the future of global connectivity-we're building it. From architecting and amplifying the reach of a private, global, multi-cloud IP network, to bringing hyperlocal edge technology right to your fingertips through intuitive APIs, we're shaping a new era of seamless interconnection between people, devices, and applications.

We're driven by a desire to transform and modernize what's antiquated, automate the manual, and solve real-world problems through innovative connectivity solutions. As a testament to our success, we're proud to stand as a financially stable and profitable company. Our robust profitability allows us not only to invest in pioneering technologies but also to foster an environment of continuous learning and growth for our team.

Our collective vision is a world where borderless connectivity fuels limitless innovation. By joining us, you can be part of laying the foundations for this interconnected future. We're currently seeking passionate individuals who are excited about the opportunity to contribute to an industry-shaping company while growing their own skills and careers.

語学要件：日本語・英語ともにビジネスレベル必須

The Role

We’re building a local Enterprise Sales Pod in Tokyo - one AE and one Forward Deployed Engineer (FDE), working together to build a Telnyx enterprise business in your market. You’ll embed directly with enterprise customers to architect and ship production systems on Telnyx’s global network - voice, messaging, AI, and wireless.

This isn’t about demoing products. It’s about building real solutions that work at scale.

You’ll work side-by-side with a dedicated Enterprise AE - not a demo resource, but a commercial partner who owns the named-account list, builds executive relationships, and closes the deal. You own the technical side: discovery, architecture, POC, and production go-live. You win together. No throw-over-the-wall.

製品デモが仕事ではありません。実際にスケールするソリューションを作ることが仕事です。

- ディスカバリー、アーキテクチャ設計、POC、本番稼働まで。成果は二人のものです。「あとはそちらで」という引き渡しはありません。

The Pod Model

Enterprise AE - owns the named-account list, builds executive relationships, gets in the room, owns commercial qualification and close, expands the account.

Forward Deployed Engineer - owns technical discovery, designs the architecture, builds the POC when gated, gets the first workload live, removes blockers and finds the next workload.

We sell the workload, not the SKU. Customers buy a production outcome - an AI contact center, a SOC/NOC agent, global communications, connected mobility, or enterprise inference - that runs on Telnyx primitives (voice, messaging, numbers, wireless, Voice AI, inference, agents, connectivity). You lead with the outcome conversation, not a product menu.

エンタープライズAE - 担当アカウントリストを保有し、経営層との関係を構築し、商談の場を作り、商務面の見極めとクロージングを担い、アカウントを拡大します。

フォワードデプロイドエンジニア -

私たちが売るのはSKUではなくワークロードです。お客様が購入するのは本番環境での成果 - AIコンタクトセンター、SOC/NOCエージェント、グローバル通信、コネクテッドモビリティ、エンタープライズ推論 - であり、それらはTelnyxのプリミティブ（音声、メッセージング、電話番号、ワイヤレス、Voice AI、推論、エージェント、コネクティビティ）上で動きます。製品メニューではなく、成果の対話から入ってください。

What You’ll Do

• Embed with enterprise customers to understand their communications workflows, AI use cases, and integration challenges firsthand

• Build and deploy custom implementations: AI Voice Assistants, Telnyx APIs (Voice, Messaging, Fax, Wireless), WebRTC

• Run open-weight LLMs in customer environments - consume GLM, Kimi, DeepSeek, Qwen, and MiniMax through Telnyx Inference (OpenAI-compatible API; there’s no model infrastructure for you to run), or deploy self-hosted stacks (Llama, Mistral, and region-specific models like Swallow, PLaMo, or other Japanese-language sovereign models) behind your own serving engine when air-gapped or sovereign-cloud requirements demand it

• Deploy and operate LiteLLM as the model gateway in customer environments: a unified OpenAI-compatible interface across self-hosted open-weight models and hosted providers, with routing, load balancing, retries and fallbacks, rate limits, and per-team virtual keys

• Instrument and govern LLM usage through the gateway - cost tracking and budgets, caching, logging and observability (OpenTelemetry, Langfuse, or similar), and guardrails - so customers can see and control what their AI workloads are doing

• Wire production observability for everything you ship - metrics, logs, traces, dashboards, and alerting (e.g. Prometheus + Grafana for metrics, OpenTelemetry for traces, Graylog or ELK for logs - or the customer’s existing stack) - so you and the customer’s ops team both know what “healthy” looks like and what pages whom when it isn’t

• Design model routing strategies for real-time voice workloads, balancing latency, cost, and quality, with sane fallback behavior when a provider degrades

• Make the build-vs-buy case between self-hosted open-weight models and hosted frontier APIs, and keep the customer’s application code portable across both

• Adapt models to customer domains: prompt and RAG pipelines and evaluation harnesses for Japanese and English language use cases and Japan/APAC-specific regulatory environments (APPI, data localization, METI/FSA cloud regulations)

• Lead POCs, pilots, and production launches from whiteboard to go-live

• Own customer outcomes - stay engaged until the solution is live and stable

• Collaborate directly with Product and Engineering to shape the roadmap based on field insights from Japan and the broader APAC region

• Create clear technical documentation, runbooks, and maintainable solutions for handoff

• Troubleshoot and resolve complex integration issues alongside customer teams

• エンタープライズのお客様に入り込み、通信ワークフロー、AIユースケース、連携上の課題を現場で直接理解する

• カスタム実装の構築とデプロイ：AIボイスアシスタント、Telnyx API（Voice、Messaging、Fax、Wireless）、WebRTC

• お客様環境でオープンウェイトLLMを稼働させる - Telnyx

• ゲートウェイ経由でLLM利用を可視化・統制する - コスト追跡と予算管理、キャッシュ、ロギングとオブザーバビリティ（OpenTelemetry、Langfuse など）、ガードレールを整備し、お客様が自社のAIワークロードの挙動を把握・制御できるようにする

• 納品するすべてに本番オブザーバビリティを組み込む - メトリクス、ログ、トレース、ダッシュボード、アラート（例：メトリクスはPrometheus +

• POC、パイロット、本番ローンチを、ホワイトボードの段階から稼働開始まで主導する

• お客様の成果に責任を持つ - ソリューションが安定稼働するまで関わり続ける

• 日本およびAPAC地域の現場知見をもとに、プロダクト・エンジニアリングチームと直接連携し、ロードマップ策定に関与する

• 引き継ぎを前提とした、明確な技術ドキュメント、ランブック、保守しやすいソリューションを作成する

• お客様のチームと並走し、複雑な連携上の問題をトラブルシュートし解決する

What We’re Looking For

• Business-level Japanese and professional working proficiency in English - both required. You’ll run whiteboard sessions, live troubleshooting, and escalations with customer engineering teams in Japanese, and work day-to-day with a globally distributed team in English.

• 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

• 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

• 日本語：ビジネスレベル（必須）／英語：ビジネスレベル（必須）。

• コンピュータサイエンスの学位、または同等の実務経験

• 本番ソフトウェアの開発・リリース経験3年以上 -

• 複数言語での開発力：Python、Node.js/TypeScript、Go - すべてが同水準である必要はありません（Telnyx Edge Compute（関数およびステートフルアクター）はTypeScriptのため、同言語は特に有用です）

• Kubernetes上でのコンテナ化サービスのデプロイ経験。シークレット管理、設定管理、アップグレードまで含めて担えること

• オブザーバビリティを自ら構築し、そのアラートで実際に呼び出された経験（Prometheus + Grafana、OpenTelemetry、Graylog、ELK など）。何を監視し、何をアラートにし、「正常」とはどういう状態かを理解していること

• 高並行処理の経験 -

• APIを利用するだけでなく、ゼロから設計・構築した経験 - OpenAPI仕様、REST/GraphQL設計、認証、レート制限、バージョニング、冪等性

• イベント駆動の思考と、クラウドネイティブな感覚

• SIP、WebRTC、またはリアルタイム音声・メッセージングシステムに触れた経験

• 自走できること - 背後にエンジニアリングチームはいません。コードとドキュメントを自分で読み、（上司ではなく）お客様に質問し、技術的な判断を自分で下せること

• 顧客対応のエンジニアリング経験 - 同じ週のうちに、お客様のエンジニアとディスカバリーを実施し、経営層にプレゼンできること

• 「動かない」という一言を、根本原因まで落とし込める力

• お客様先での業務、および重要度の高い技術的な議論に抵抗がないこと

• 東京在住、または転居可能であること - ハイブリッド勤務で、日本国内およびAPAC地域への出張があります

• 日本での就労資格を有すること、またはビザサポートの対象となること

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)

• AIボイスアシスタント、STT/TTS、またはLLMベースの対話システムの経験

• 特定ドメイン向けの評価セット構築経験

• LLMゲートウェイの本番運用経験（LiteLLM、Portkey、Kong AI Gateway、または自社開発のOpenAI互換プロキシ）- 設定ファイル駆動のモデル定義、ルーティング・フォールバックルール、仮想キー管理を含む

• ゲートウェイ配下の推論サービングエンジンの経験 - 本番サービングにはvLLM、SGLang、TGI、軽量なオンプレミス用途にはOllama - および、セルフホストモデルのGPU容量見積り（KVキャッシュの使用量、同時バッチサイズ、VRAMに対するコンテキスト長）

• SQLの習熟（Postgres、MySQL、Oracle）

• ETLおよびデータ加工の経験

• CI/CDパイプラインの設計と自動化

• 通信、CPaaS、または高成長SaaS領域でのバックグラウンド

• セキュリティ意識（IAM、暗号化、監査ログ）