Conversational AI Engineer (Senior)

Vor 30+ Tagen
Munich
Vollzeit
Geschätztes Gehalt

Das könntest du laut kununu User:innen als Leiter:in Systementwicklung in Deutschland verdienen

Ø 100.700 €
Bruttodurchschnittsgehalt Vollzeit
58.600 €170.900 €
Was die Firma über den Job sagt

Conversational AI Engineer

Type: Full-time

Location: Munich (preferred), hybrid/flexible

Overview

As a Conversational AI Engineer within Advanced Analytics (DA3) in the Chief Data & AI Office at Allianz Partners, you will design, build, and operate voice agents and conversational AI systems that power customer-facing and operational use cases at scale.

We are looking for an engineer with deep hands-on experience in agent building - not just platform configuration - who can architect multi-turn dialogue systems, integrate them with live backend services, and own their quality and reliability in production.

You will work in a cross-functional environment with Computational Linguists, Backend Engineers, and product teams, taking end-to-end ownership of voice agent delivery - from conversation design and NLU integration through to API wiring, observability instrumentation, and production operation.

You will also build reusable agent components and patterns that raise the capability of the whole team and use AI-assisted developer tools as a standard part of how you work.

Key Responsibilities

  • Design, build, and operate voice agents and multi-turn conversational flows, owning quality and reliability end-to-end
  • Architect agent logic including intent routing, context management, dialogue state handling, fallback and escalation paths, and graceful error recovery
  • Integrate voice agents with backend services via REST APIs to retrieve live data, trigger business processes, and handle asynchronous responses
  • Configure and tune speech pipeline components including ASR, TTS, and voice activity detection to meet accuracy and latency targets
  • Instrument voice agents for observability, including:
    • Conversation analytics
    • Containment rates
    • Drop-off points
    • Error logging
    • Alerting on quality regressions
  • Build reusable dialogue components, shared templates, and platform patterns to accelerate delivery across use cases
  • Collaborate with Computational Linguists to improve NLU quality, intent coverage, and entity extraction accuracy
  • Diagnose and resolve issues across dialogue logic, NLU performance, and API integrations; perform root-cause analysis
  • Contribute to design reviews, define quality standards, and support knowledge sharing across the team

Required Experience and Skills

  • 5+ years of professional experience in conversational AI, voice agent development, or dialogue systems engineering, with production system exposure
  • Demonstrated hands-on agent building experience, including designing and implementing multi-turn dialogue systems
  • Strong NLU integration experience:
    • Intent classification
    • Entity extraction
    • Slot filling
    • Dialogue state tracking
  • Solid API integration skills:
    • REST API design and consumption
    • Authentication patterns
    • Error handling
    • Asynchronous response handling
  • Experience operating voice AI systems in production:
    • Monitoring
    • Incident response
    • Quality measurement
    • Continuous improvement
  • Proficiency in Python for tooling, integration scripting, and automation
  • Experience with conversational AI evaluation metrics:
    • Containment rate
    • Task completion
    • NLU accuracy
    • Overall conversation quality
  • Strong understanding of speech pipeline fundamentals:
    • ASR (Automatic Speech Recognition)
    • TTS (Text-to-Speech)
    • VAD (Voice Activity Detection)
    • Impact on user experience

Ways of Working

  • Comfortable in agile, iterative environments with ownership of agent quality and production reliability
  • Strong collaborator across technical and non-technical stakeholders, able to translate complex dialogue design into business terms
  • High standards for quality and craftsmanship, measured by real production performance
  • Proactive learner using AI-assisted tools (e.g., GitHub Copilot, Claude Code) to improve development speed and automation

Nice to Have

  • Experience with voice AI platform certifications or advanced configuration on major conversational AI platforms
  • Experience integrating voice agents with containerised backend services and cloud-native API infrastructure
  • Multilingual experience, particularly in European languages (German, Italian, Spanish, French)
  • Experience in regulated environments with requirements around:
    • Conversation logging
    • Data handling
    • Access controls

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