AI ML Architect

Role Description:

10+ years

Lead the design and delivery of AI solutions with a strong emphasis on Generative AI, LLMs, AI agents, and core machine learning. The role blends architecture, blueprint creation, and close collaboration with business and engineering teams

Responsibilities

• Define AI/ML architecture, establish standards, and guide teams on best-practice implementation.
• Design end-to-end AI solutions-including agentic workflows, RAG pipelines, and ML models-that seamlessly integrate with enterprise systems.
• ead technical design, proof-of-concepts, and reference implementations for AI agents and LLM-driven use cases.
• Demonstrate strong expertise in MLOps and automated ML pipelines.
• upport presales by contributing to solution architecture, work-breakdown structures, task-level decomposition, and implementation planning.

Required Skills

• Proven experience in designing and deploying enterprise-grade AI solutions.
• Strong Python expertise with hands-on work across LLMs and Generative AI, including RAG, fine-tuning, and prompt engineering, along with proficiency in at least one major cloud AI platform.
• Practical background in core machine learning workflows-data wrangling, preprocessing, model evaluation, and model selection-using frameworks such as PyTorch or TensorFlow.
• Solid understanding of MLOps principles, including model lifecycle management, deployment pipelines, and monitoring.
• Awareness of security and privacy standards, with a clear understanding of their implications for AI/ML systems