This role focuses on architecting and delivering advanced enterprise AI solutions, particularly leveraging Generative AI, agent-based systems, and LLM orchestration. The Senior AI Engineer will drive the technical vision, promote best practices, and lead innovation in creating scalable, secure, and efficient AI workflows. This position is key to advancing the company's applied AI capabilities.

The role involves leading the design and implementation of sophisticated AI systems. You will be instrumental in shaping the technical direction and ensuring the highest standards of engineering excellence within the team. This is an opportunity to make a significant impact on the company's AI strategy and execution.

Take ownership of the complete technical design and delivery lifecycle for GenAI and agentic systems, suitable for both internal and external applications. Develop multi-agent workflows using frameworks like LangChain and A2A protocols, alongside custom orchestration solutions. Guide the refinement of prompt architectures, context management strategies, and hybrid RAG pipelines. Seamlessly integrate AI services with enterprise platforms such as Azure Foundry, Databricks, and essential business systems. Lead engineering teams, mentor junior engineers, and ensure technical synergy across product and platform initiatives. Innovate on performance, latency, and accuracy through advanced research and optimization techniques. Establish reusable components, shared templates, and internal GenAI SDKs, while enforcing standards for ethical AI, context control, prompt security, and hallucination mitigation.

A minimum of 4 years of experience in AI/ML/GenAI solutioning is required, with at least 2 years in a technical leadership capacity. Essential skills include deep proficiency in Python 3 and extensive experience with libraries such as OpenAI, Pydantic, Transformers, FAISS, and LangChain. Proven ability to deploy scalable GenAI solutions incorporating cloud-native architectural principles. Solid working knowledge of Azure cloud services, GitHub workflows, and CI/CD methodologies is also a must. Experience in optimizing vector stores, managing token-level control, and enhancing prompt performance is critical for this role.