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 contemporary 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%.

📌 Principal Engineer - AI / ML ( Speech, Voice & GenAI Architecture ) (Bengaluru)
🏢 Stryker
📍 Bengaluru