Agentic AI-Sr Architect

About the Role

We are seeking an experienced Agentic AI Senior Architect to design, develop, and deploy production-grade AI/LLM solutions. The ideal candidate will have strong hands-on experience with LLMs, Agentic AI, speech/voice AI, cloud AI platforms, and Azure services, along with the ability to lead technical teams and drive AI architecture.

Responsibilities

• Design, develop, and deploy scalable AI/LLM and Agentic AI solutions.
• Build and optimize multi-agent and real-time voice AI pipelines.
• Evaluate, fine-tune, and improve model performance, reliability, and scalability.
• Collaborate with Data Engineering, Software Engineering, and LLMOps teams.
• Troubleshoot AI deployment and integration challenges.
• Research emerging AI technologies and recommend innovative solutions.
• Mentor junior AI engineers and review code, models, and architectures.
• Communicate AI concepts and technical findings to technical and non-technical stakeholders.
• Work in Agile/Scrum environments using tools such as Jira or Azure DevOps.

Requirements

• Bachelor's/Master's degree in Computer Science, AI/ML, Data Science, or related field.
• 6-10 years of AI/ML/Deep Learning experience.
• 2-3 years of hands-on experience with LLMs, NLP, Speech/Voice AI, or real-time voice pipelines.
• 3-5 years deploying AI solutions in production.
• 5+ years with Python, PyTorch, TensorFlow, or similar frameworks.
• 3-5 years designing, training, and fine-tuning AI/LLM or speech/voice models.
• 5 years of experience with AWS SageMaker, Azure ML, or GCP AI.
• 2+ years with Agentic AI frameworks such as LangChain, LangGraph, MCP, A2A, and multi-agent orchestration.
• Experience with model evaluation, optimization, bias detection, and performance tuning.
• Strong experience integrating AI models into applications through APIs and pipelines.
• 2-3 years of experience with Azure AI services, including Azure OpenAI, Azure AI Speech, Translator, AI Search, AKS/Container Apps, API Management, Event Hubs, Key Vault, and Application Insights.

Qualifications

• Advanced LLM techniques, prompt engineering, and fine-tuning (preferred).
• Responsible AI, ethics, fairness, and bias mitigation (preferred).
• LLMOps, including model evaluation, tracing, CI regression testing, cost telemetry, model routing, and drift detection (preferred).
• Evaluation metrics such as WER, Entity F1, and COMET (preferred).

Location: Santa Clara, CA
Duration: Full-time