About the job
We are hiring for great (Senior) AI Engineer who are open to learning the tools we use and building the AI Platform at First American. Role Summary : As an AI Engineer in our Centre of Excellence, you will be instrumental in building, deploying, and maintaining production-ready AI applications using readily available foundation models . You will bridge the gap between model development and practical application, ensuring robust, scalable, and efficient AI systems that deliver tangible value. Key Responsibilities: • Design and implement end-to-end AI systems, integrating foundation models into various applications and workflows. • Apply and optimize model adaptation techniques, including prompt engineering, Retrieval-Augmented Generation (RAG), and finetuning, to tailor foundation models for specific use cases. • Develop and integrate AI architecture components such as context enhancement, input / output guardrails, model routers / gateways, caching mechanisms, and agent patterns to ensure system reliability and security. • Implement AI pipeline orchestration to define and chain together different components of an AI system, ensuring seamless data flow and complex workflow execution. • Optimize AI model inference for latency and cost, utilizing techniques like quantization, distillation, and parallelism, and demonstrate proficiency in working with GPUs and large compute clusters. • Collaborate closely with Data Scientists to integrate trained models and with Data Engineers to ensure efficient data pipelines for AI applications. • Contribute to defining and implementing systematic evaluation pipelines for AI applications, focusing on metrics such as factual consistency, generation capability, and instruction-following for open-ended outputs. • Engage in continuous monitoring and observability of AI systems in production to detect failures, drifts, and identify opportunities for improvement and cost savings. • Assist in productizing AI-powered outputs and features, ensuring alignment with customer needs and product strategy. Required Skills & Qualifications: • Proven experience in building applications with foundation models and deploying AI systems into production environments. • Strong proficiency in prompt engineering, RAG, and finetuning techniques for model adaptation. • Familiarity with AI architecture patterns and their practical implementation. • Understanding of inference optimization techniques and experience with high-performance computing environments (e.g., GPUs). • Knowledge of AI evaluation methodologies for open-ended models and experience in setting up robust evaluation pipelines. • Proficiency in programming languages commonly used in AI development, such as Python, with an understanding of relevant APIs and frameworks. • Ability to work in an iterative, experimental environment and adapt to rapidly changing model capabilities and tools. • Excellent communication and collaboration skills for working with diverse, cross-Functional teams.
Requirements
- foundation models
- model adaptation
- prompt engineering
- RAG
- inference optimization
- high-performance computing
- Python
Preferred Technologies
- foundation models
- model adaptation
- prompt engineering
- RAG
- inference optimization
- high-performance computing
- Python
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