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Jobs(26,992)/Frontend Engineer Role(251)/Telnyx (19) - 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
Telnyx

Telnyx - 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

Tokyo, Japan - Hybrid3w ago
In OfficeMidAPACFintechArtificial IntelligenceFrontend EngineerSupport EngineerRemote AssistantGoPythonNode.jsTypeScriptCustomer Engagement

Requirements

• 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. • Business-level Japanese and professional working proficiency in English — both required. • 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)。 お客様のエンジニアリングチームとは日本語でホワイトボードセッション、ライブでのトラブルシューティング、エスカレーション対応を行い、社内のグローバルチームとは日常的に英語で業務を進めます。 • 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 — 実ユーザーが依存するコードを書き、そのオンコール対応を担い、障害時にデバッグした経験があること(上記に当てはまる方であれば、コンサルティング出身も対象となります) • 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) • 本番環境においてモデルの手前で何が壊れるかの実践的な理解:プロバイダーのレート制限とクォータ、タイムアウトとリトライの挙動、ストリーミング、トークン計上とコスト按分、そして並行処理下でのみ顕在化する障害モード • 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 — 実運用規模でのKafka、メッセージキュー、イベントストリーム。スループットが急増したときに何が壊れるか(コンシューマーラグ、バックプレッシャー、ホットパーティション、リバランスの停滞)と、何がそれを吸収するか(パーティショニング、コンシューマーグループ、パーティション数までの並列化)を理解していること • 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 • 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 • オープンウェイトモデルの動向、および地域特化モデルと多言語モデルのトレードオフに関する知見。日本語モデル(Swallow、PLaMo、ELYZA、Rinna)や日本のソブリンAI関連の取り組みを含む • 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) • 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 • ソブリンクラウドまたはオンプレミス環境へのデプロイ経験、および日本/APACの規制フレームワークへの理解(APPI(個人情報保護法)、経産省クラウドセキュリティガイドライン、金融庁の金融機関向けクラウド外部委託ガイドライン、日本のデータローカライゼーション要件、APAC域内の越境データ移転フレームワーク) • セキュリティ意識(IAM、暗号化、監査ログ)

Responsibilities

• Troubleshoot and resolve complex integration issues alongside customer teamsWhat 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 sponsorshipBonus 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)

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