Design and build data and AI infrastructure systems including model selection and versioning, indexing, feedback capture, monitoring, and performance.
Integration : Implement AI solutions that integrate seamlessly with existing business systems and enhance functionality. Work with systems and application owners to design complementary AI solutions.
Collaboration : Work with data scientists, enterprise architects, and stakeholders to develop and deploy AI models based on use cases and value.
Operations : Ensure scalability, reliability, and security of AI and data orchestration systems. Design systems to produce ethical, un-biased output.
Governance and Improvement : Monitor and improve AI systems based on performance metrics and user feedback. Implement governance and observation methodologies to provide transparency to model operations.
REQUIREMENTS
Proven experience as a Data Engineer, AI Engineer, or similar role, with a focus on production, customer facing implementation of data orchestration and AI technologies.
Strong ability to translate use case and business domain functions to production applications o Proficiency in programming languages (Python, Java) and related AI / ML frameworks (ex. LangChain, TensorFlow, PyTorch).
Experience with prompt flows, prompt engineering best practices, and AI patterns (ex. Retrieval Augmented Generation (RAG)) o Development and production deployment experience with data products on public cloud platforms (Azure and AWS preferred) o Knowledge of vector databases, search indexes, and embeddings.
Experience with fine-tuning (PEFT) is a plus o Experience with API architecture and design is a plus.
Education : Bachelor's degree in Computer Science, Engineering, or a related field.
Certifications : Relevant certifications in AI, data engineering, or cloud computing are a plus.
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