Senior Solutions Architect

Accountabilities: Lead the architecture and implementation of enterprise deployments involving speech-to-text, text-to-speech, and voice-agent technologies. Own post-sales technical success for assigned EMEA customers, helping unblock integrations, improve accuracy and latency, and achieve stable production deployments. Act as a Tier-3 technical escalation point, leading root-cause analysis, developing mitigations, and creating durable fixes or automation where appropriate. Design reference architectures and repeatable implementation patterns for use cases such as contact centers, voice analytics, quality assurance, and AI agents. Build practical samples, scripts, internal tools, and other reusable assets that simplify customer implementations and internal workflows. Support pre-sales discovery and proof-of-concept engagements where deeper technical expertise is required, translating business objectives into concrete technical plans and measurable success criteria. Partner with Product and Engineering teams to communicate customer feedback, prioritize fixes and features, and influence the product roadmap. Develop and maintain runbooks, playbooks, deployment guides, troubleshooting resources, and other knowledge assets that scale technical expertise across regions. Participate in regional on-call and incident-response rotations, helping maintain agreed customer support levels and service expectations. Collaborate with global teams across EMEA, the Americas, and APAC to provide continuous technical coverage and consistent customer experiences. Travel within the region approximately 10–20% of the time for critical customer milestones when required. Requirements 5+ years of experience in Solutions Architecture, Solutions Engineering, or a comparable customer-facing technical role. Professional software engineering experience in at least one language such as Python, Rust, or JavaScript, with the ability to build production-quality proof-of-concepts and tools. Hands-on experience with modern cloud platforms, containerization, and orchestration technologies such as Docker and Kubernetes. Strong understanding of secure network design and API-driven systems. Demonstrated ownership of complex post-sales initiatives, including production deployments, migrations, performance optimization, and incident response. Ability to work comfortably across application code, containers, cloud infrastructure, APIs, and production environments. Excellent written and verbal communication skills, with the ability to communicate effectively with both technical specialists and executive stakeholders. Strong problem-solving skills and an ability to translate ambiguous customer requirements and operational constraints into clear architectures and implementation plans. Familiarity with GDPR, data privacy, enterprise security reviews, authentication, authorization, and data residency considerations relevant to EMEA customers. Experience with speech recognition, text-to-speech, or voice agents integrating LLMs is highly valued. Knowledge of WER analysis, model selection and tuning, and accuracy-versus-latency trade-offs is advantageous. Experience operating self-hosted systems, including Helm-based deployments and production observability, is a plus. Fluency in an additional European language such as German, French, Dutch, Italian, or Spanish is advantageous. Comfortable working remotely from Germany or another eligible EMEA location with reliable overlap with customer business hours. Benefits Fully remote work across EMEA, with periodic regional team meetups. Opportunity to work on complex, production-grade AI voice technologies and enterprise deployments. Collaboration with international colleagues across EMEA, the Americas, and APAC. Exposure to the full customer lifecycle, spanning pre-sales, architecture, implementation, production support, and product feedback. Practical, hands-on environment with defined escalation paths, shared playbooks, and measurable service expectations. Opportunities to create reusable technical assets, automation, documentation, and implementation patterns with impact across the wider organization. Regional travel opportunities for important customer engagements, estimated at 10–20%. A fast-moving environment that encourages experimentation, continuous learning, and effective use of modern AI tools.