Principal Engineer - AI / ML ( Speech, Voice & GenAI Architecture )

Vocera, now part of Stryker, is seeking a highly experienced and visionary Principal Engineer AI/ML to lead the architecture, strategy, and technical direction of our AI-powered speech and voice intelligence platforms.

This role serves as the AI/ML Architect for real-time speech, conversational AI, and GenAI-driven clinical communication systems. You will define long-term technical vision, establish scalable AI architecture patterns, and guide engineering teams in delivering reliable, secure, and high-performance AI systems deployed at enterprise scale on Microsoft Azure.

This is a hands-on architectural leadership role requiring deep expertise in speech technologies, modern ML/LLM systems, distributed architecture, and cloud-native AI platforms.

What You Will Do
AI/ML Architecture & Technical Strategy

• Define and own the end-to-end AI/ML architecture for speech, voice intelligence, and GenAI platforms.
• Establish scalable patterns for real-time speech processing (low-latency ASR, TTS, streaming pipelines).
• Architect RAG-based systems, LLM orchestration layers, semantic search, and conversational AI frameworks.
• Drive design decisions across model hosting, inference optimization, observability, reliability, and cost efficiency.
• Define evaluation frameworks for model quality, accuracy, bias, hallucination control, and safety.

Platform & System Design

• Design enterprise-grade, cloud-native AI systems on Microsoft Azure.
• Lead architectural decisions for:
  • Model lifecycle management
  • Multi-model orchestration
  • Feature stores and vector databases
  • High-throughput inference pipelines
  • Secure data handling in healthcare environments
• Ensure systems meet performance SLAs (latency, throughput, error rates) and compliance requirements.
• Drive multi-region scalability and disaster recovery strategy for AI workloads.

Speech & Voice Intelligence Leadership

• Architect solutions for:
  • Real-time speech-to-text and text-to-speech
  • Domain-adapted ASR models
  • Intent recognition and entity extraction
  • Conversational AI assistants
  • Summarization and contextual intelligence
• Define strategies for handling accents, noisy environments, and healthcare-specific terminology.
• Guide model fine-tuning and adaptation for clinical communication use cases.

GenAI & LLM Systems

• Lead adoption of LLM-based architectures including:
  • RAG pipelines
  • Prompt orchestration frameworks
  • Guardrails and safety layers
  • Evaluation and monitoring systems
• Define best practices for prompt engineering, model benchmarking, and production hardening.
• Drive responsible AI practices including governance, auditability, and compliance.

Engineering Leadership & Influence

• Provide architectural guidance across multiple pods and teams.
• Review and approve technical designs impacting AI systems.
• Mentor senior engineers and elevate AI engineering maturity across the organization.
• Partner with Product, UX, Security, DevOps, and Platform teams to align AI capabilities with business strategy.
• Participate in customer and executive discussions to translate technical vision into business value.
• Drive innovation initiatives, patents, and strategic technical investments.

Required Qualifications

• Bachelors or Masters degree in Computer Science, Engineering, AI, or related field.
• 12+ years of experience in software engineering with substantial experience in AI/ML systems.
• 6+ years of experience designing and deploying production-grade AI/ML architectures.
• Deep expertise in speech technologies (ASR/TTS), NLP, and modern LLM systems.
• Strong proficiency in Python and AI frameworks (PyTorch, TensorFlow, etc.).
• Proven experience architecting AI workloads on Microsoft Azure.
• Strong background in distributed systems, backend architecture, APIs, and data pipelines.
• Demonstrated experience leading architecture decisions across multiple teams.

Preferred / Strongly Desired Qualifications
AI / ML & GenAI

• Hands-on experience with Azure OpenAI, Azure ML, and enterprise LLM deployments.
• Experience designing RAG architectures with vector databases and semantic search.
• Expertise in model evaluation frameworks, ML observability, and performance tuning.
• Experience adapting or fine-tuning speech models for domain-specific use cases.
• Familiarity with LangChain, MLflow, prompt evaluation tooling, and model governance frameworks.

Cloud & Platform

• Deep experience with:
  • Azure OpenAI
  • Azure ML
  • Azure AI Search
  • Azure Functions / Container Apps
  • Kubernetes-based model serving
• Experience with CI/CD for ML systems (MLOps best practices).
• Exposure to AWS or GCP AI services is a plus.

Healthcare / Enterprise Systems

• Experience building secure, compliant systems in regulated environments.
• Understanding of PHI handling, data privacy, and enterprise-grade security controls.

Travel Percentage: 10%.