Agentic AI Sr Architect with Azure

Required Skills & Experience

• 6–10 years of experience in AI/ML/Deep Learning model development.
• 5+ years of experience with Cloud AI platforms such as AWS SageMaker, Azure ML, or Google Cloud Platform AI.
• 2–3 years of hands-on experience with LLMs, NLP, or Speech/Voice AI systems, including deploying AI solutions in production environments.
• 3–5 years of experience designing, training, and fine-tuning LLMs or AI models, including Speech/Voice AI systems and real-time voice pipelines.
• 2+ years of experience with Agentic AI frameworks, including LangChain, LangGraph, A2A, MCP, and multi-agent orchestration.
• 2–3 years of experience with model evaluation metrics, bias detection, and model optimization.
• 5+ years of experience integrating AI models into applications through APIs and pipelines.
• 5+ years of experience with Python, PyTorch, TensorFlow, or similar frameworks.
• 2–3 years of experience with Azure AI services, including:

·        

• Azure AI Speech & Translator
• Azure OpenAI
• Azure AI Search
• Azure Container Apps / AKS
• API Management
• Event Hubs
• Key Vault
• Application Insights

Secondary / Preferred Skills

• Advanced LLM techniques, prompt engineering, and fine-tuning strategies.
• Continuous learning and awareness of emerging AI frameworks and architectures.
• Knowledge of AI ethics, fairness, and responsible AI deployment.
• Experience with LLMOps, including:

·        

• Layered evaluations
• WER, Entity F1, and COMET
• CI regression gates
• Tracing
• Cost-per-minute telemetry
• Model routing
• Drift detection

Role & Responsibilities

• Design, develop, and deploy advanced AI models aligned with business requirements.
• Research emerging AI/ML technologies and recommend innovative solutions.
• Evaluate model performance, perform fine-tuning, and ensure scalability, reliability, and production readiness.
• Collaborate with Data Engineering, LLMOps, and Software Engineering teams to deliver end-to-end AI solutions.
• Clearly communicate AI concepts, model behavior, and technical findings to both technical and non-technical stakeholders.
• Mentor junior AI engineers and review code, models, and technical implementations for best practices.
• Identify bottlenecks in model performance and proactively develop solutions.
• Troubleshoot AI deployment, integration, and production challenges.
• Analyze data patterns and model outputs to generate actionable insights.
• Apply structured thinking to optimize AI workflows and pipelines.
• Present complex model results in a concise, clear, and actionable manner.
• Collaborate effectively with cross-functional teams.
• Provide constructive feedback and mentor junior team members.
• Demonstrate strong problem-solving and analytical thinking.
• Work effectively within Agile/Scrum environments, with exposure to tools such as Jira and Azure DevOps.
• Provide regular updates and demonstrate proactive ownership, diligence, and strong follow-through.