Agentic AI-Sr Architect

Bachelor’s or Master’s degree in Computer Science, AI/ML, Data Science, or related field
Advanced coursework or certifications in machine learning, deep learning, or NLP
Strong mathematical and statistical foundation

6–10 years of experience in AI/ML/Deep Learning model development
2-3 years Hands-on experience with LLMs, NLP, or speech/voice AI systems
3-5 years of experience deploying AI solutions in production environments

5+ years of experience in Python, PyTorch, TensorFlow, or similar frameworks
3-5 years of experience designing, training, and fine-tuning large language models or AI models, speech/voice AI systems, Realtime voice pipeline
5 years of experience in cloud AI platforms (AWS Sagemaker, Azure ML, Google Cloud Platform AI)
2+ years of experience in Agentic AI frameworks such as LangChain, LangGraph, A2A, MCP, and Multi agent orchestration
2-3 years of experience Familiarity with model evaluation metrics, bias detection, and optimization
5 years of experience in  integrating AI models into applications via APIs or pipelines
2-3 years experience in Azure services — Azure AI Speech and Translator, Azure OpenAI, AI Search, plus Container Apps/AKS, API Management, Event Hubs, Key Vault, and Application Insights

Key technical skills :
Design, develop, and deploy advanced AI models to meet business requirements
Collaborate with data engineers, LLM Ops, and software teams for end-to-end solutions
Evaluate model performance, fine-tune, and ensure scalability and reliability
Research emerging AI/ML technologies and propose innovative solutions
Mentor junior AI engineers and review code/models for best practices

Communication Skills:
Clearly explain AI concepts and model behavior to technical and non-technical stakeholders
Present complex model results in a concise and actionable manner
Interpersonal Skills:
Collaborate effectively with cross-functional teams
Provide constructive feedback and mentor junior team members
Problem-Solving and Analytical Thinking:
Identify bottlenecks in model performance and propose solutions
Troubleshoot deployment or integration challenges proactively
Analyze data patterns and model outputs to derive insights
Apply structured thinking to optimize AI workflows and pipelines
Task/ Work Updates
Prior experience in working on Agile/Scrum projects with exposure to tools like Jira/Azure DevOps
Provides regular updates, proactive and due diligent to carry out responsibilities

Advanced LLM techniques, prompt engineering, and fine-tuning strategies
AI ethics, fairness, and responsible AI deployment
Continuous learning on emerging AI frameworks and architectures
LLMOps - layered evals (WER, entity F1, COMET), CI regression gates, tracing, cost-per-minute telemetry, model routing, and drift detection.