In this role, you'll architect and implement machine learning solutions that power intelligent business automation. Your technical scope spans designing generative AI models using modern frameworks, fine-tuning large language models for specific applications, and establishing robust data pipelines for training and evaluation. You'll own the complete lifecycle—from research and prototyping through production monitoring and iterative optimization. Beyond model work, you'll engineer sophisticated automation systems using orchestration tools and API integrations to connect AI capabilities with existing enterprise infrastructure. This includes prompt engineering, context optimization for conversational systems, and building quality assurance frameworks for agent-based solutions. You'll collaborate across engineering, product, and client teams to embed AI capabilities into platforms and services. As you grow in the role, you're expected to mentor junior engineers and contribute architectural guidance on complex technical decisions. The position requires proficiency in Python, cloud platforms, and modern ML frameworks, combined with a pragmatic approach to shipping production systems. You should stay current with advancements in transformer architectures, LLMs, and agentic AI patterns while maintaining focus on delivering measurable client outcomes.