Senior LLM AI Architect – Speech & Voice AI
Location: Santa Clara, CA
Work Arrangement: Onsite
Employment Type: Full-Time (or) Contract-to-Hire
Experience Required: Minimum 12+ Years
Job Overview
We are looking for an experienced Senior LLM AI Architect with strong hands-on expertise in Large Language Models (LLMs), Speech/Voice AI, Multi-Cloud AI platforms, and enterprise AI architecture.
The ideal candidate will have experience designing, developing, fine-tuning, integrating, and deploying production-ready AI/ML solutions, including real-time voice pipelines, Retrieval-Augmented Generation (RAG), Agentic AI, and multi-agent orchestration.
The candidate must demonstrate strong architectural knowledge and hands-on implementation experience across cloud AI platforms, particularly AWS, Azure, and Google Cloud Platform.
Key Responsibilities
Design, develop, and deploy advanced AI/ML models to meet business requirements.
Architect and implement LLM-based applications, RAG solutions, and Agentic AI workflows.
Design and develop speech/voice AI systems and real-time voice processing pipelines.
Implement LLM orchestration and multi-agent architectures.
Integrate AI models into enterprise applications using APIs, custom connectors, and pipelines.
Deploy and manage AI solutions across cloud platforms.
Evaluate model performance, fine-tune models, and optimize scalability and reliability.
Collaborate with Data Engineering, LLM Ops, and Software Engineering teams.
Research emerging AI/ML technologies and recommend innovative solutions.
Mentor junior AI engineers and review code, models, and architectural implementations.
Mandatory Technical Skills & Experience
Candidates must demonstrate the following experience, with the relevant skills reflected in their resumes and project descriptions.
Overall Experience: Minimum 12+ years of professional experience.
AI/ML Development: 6–10 years of experience in AI/ML/Deep Learning model development.
LLM / NLP / Speech AI: 2–3 years of hands-on experience with LLMs, NLP, or Speech/Voice AI systems.
Production AI Deployment: 3–5 years of experience deploying AI solutions in production environments.
Python & AI Frameworks: 5+ years of experience with Python, PyTorch, TensorFlow, or similar frameworks.
LLM & Speech Model Development: 3–5 years of experience designing, training, and fine-tuning LLMs or AI models, including Speech/Voice AI systems and real-time voice pipelines.
Cloud AI Platforms: 5 years of experience with AWS SageMaker, Azure ML, and/or Google Cloud Platform AI platforms, including multi-cloud environments.
Agentic AI: 2+ years of hands-on experience with LangChain, LangGraph, A2A, MCP, and multi-agent orchestration frameworks.
Model Evaluation: 2–3 years of experience with model evaluation metrics, bias detection, and model optimization.
AI Integration: 5 years of experience integrating AI models into enterprise applications through APIs and pipelines.
Azure AI Services: 2–3 years of experience with Azure AI Speech, Azure Translator, Azure OpenAI, Azure AI Search, Container Apps/AKS, API Management, Event Hubs, Key Vault, and Application Insights.
LLM Architecture: Strong hands-on experience designing LLM architectures and Retrieval-Augmented Generation (RAG) solutions.
Kubernetes: Hands-on experience deploying and managing AI workloads using Kubernetes.
Required Qualifications
Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, or a related field.
Advanced coursework or certifications in Machine Learning, Deep Learning, or NLP.
Strong mathematical and statistical foundation.
Demonstrated experience designing, developing, and deploying enterprise AI solutions.
Strong analytical, troubleshooting, and problem-solving skills.
Excellent communication and stakeholder management skills.
Experience mentoring junior engineers and collaborating with cross-functional teams.
Preferred Skills
Advanced certifications in AI/ML, Deep Learning, or NLP.
Experience working in Agile/Scrum environments.
Exposure to Jira and Azure DevOps.
Experience presenting AI architecture, model behavior, and technical results to business and technical stakeholders.
Communication & Collaboration
Ability to explain AI concepts and model behavior to technical and non-technical stakeholders.
Present complex model results clearly and effectively.
Collaborate with cross-functional engineering teams.
Provide technical guidance and constructive feedback to junior engineers.
Proactively identify performance bottlenecks and resolve deployment or integration challenges.
Provide regular project updates and maintain strong ownership of assigned responsibilities.
Work Arrangement
This is an onsite opportunity based in Santa Clara, California. Candidates must be able to work onsite at the specified location.
Application Instructions
Interested and qualified candidates are requested to share their updated resume, current location, contact number, visa status, and relevant experience in the required technical skills.
Important: Please ensure the resume clearly mentions the number of years of experience in each mandatory skill, with supporting project-level experience.
