Responsibilities
- Architect and implement scalable artificial intelligence systems leveraging contemporary machine learning frameworks and large language model technologies.
- Construct and manage platform features that support fast iteration, release, monitoring, and oversight of AI-driven workloads.
- Engineer and refine Retrieval-Augmented Generation workflows and intelligent agents tailored for enterprise applications.
- Unify and manage services from multiple large language model providers and AI platforms such as OpenAI, Anthropic, and Azure OpenAI.
- Develop modular AI tools, application programming interfaces, software development kits, and reusable platform elements for internal engineering use.
- Establish comprehensive monitoring, assessment, and visibility mechanisms for AI models and system behavior.
- Work closely with multidisciplinary teams to shape AI use cases, define technical specifications, and plan delivery timelines.
- Support MLOps and AI operations including automated pipelines, model lifecycle processes, infrastructure as code, and governance protocols.
- Ensure all AI implementations align with enterprise benchmarks for security, performance, fault tolerance, regulatory compliance, and cost control.
- Promote effective practices in prompt design, model validation, safety controls, and ethical AI principles.
- Guide and develop software engineers, fostering technical advancement across the engineering community.
- Maintain active awareness of evolving AI research, tools, and market developments.
