Senior Solution Architect - Voice

DeepL DeepL · AI Frontier · Tokyo, Japan · Sales

Senior Solution Architect for DeepL Voice, focusing on designing and deploying real-time AI language solutions for enterprise clients. The role involves technical discovery, advising on end-to-end voice AI architectures (speech-to-text, text-to-speech, translation), enabling partners, and providing feedback to product and engineering teams.

What you'd actually do

  1. Lead Technical Discovery and Validation: Act as a technical expert across DeepL Voice use cases (meetings, live conversations, APIs), you will successfully engage with enterprise prospects and partners including contact centre leaders, IT architects, and CX stakeholders. Validate the art of the possible in proof-of-concepts and conduct architecture reviews to help win deals.
  2. Advise on the End-to-End Voice Architecture: Advise on scalable, real-time voice AI architectures across the full stack - speech-to-text, text-to-speech, speech-to-speech real-time translation and telephony/SIP/contact centre integrations.
  3. Enable Partners: Work with BPOs and contact centre providers to deploy, integrate, and scale voice AI globally. You'll help to build repeatable playbooks that enable partners to move fast without introducing technical risk.
  4. Close the Product Loop: You're on the front line. Bring structured, specific feedback to product and engineering on latency constraints, voice quality trade-offs, and integration gaps - and turn customer pain into roadmap influence.

Skills

Required

  • Solution Architecture
  • Solution Consulting
  • Technical Pre-Sales
  • enterprise or SaaS environments
  • SIP/VoIP/IVR
  • CCaaS Platform Architecture
  • Contact centre platforms
  • speech-to-text
  • text-to-speech
  • speech-to-speech systems
  • LLM-based conversational AI
  • WebSocket / API Integration
  • AWS Cloud Architecture
  • Japanese fluency
  • English business fluency

Nice to have

  • systems mindset
  • building technical credibility with contact centre leaders, IT and enterprise architects, and CX teams

What the JD emphasized

  • designing and deploying AI language solutions that perform in production
  • advise on scalable, real-time voice AI architectures
  • latency constraints
  • voice quality trade-offs
  • integration gaps

Other signals

  • designing and deploying AI language solutions that perform in production
  • advise on scalable, real-time voice AI architectures
  • bring structured, specific feedback to product and engineering on latency constraints, voice quality trade-offs, and integration gaps