AI Engineer

Responsibilities: Advise C-suite executives and business leaders on a broad range of technology, strategy, and policy issues associated with AI Implement generative AI models, identify insights that can be used to drive business decisions. Work closely with multi-functional teams to understand business problems, develop hypotheses, and test those hypotheses with data, collaborating with cross-functional teams to define AI project requirements and objectives, ensuring alignment with overall business goals. Conducting research to stay up-to-date with the latest advancements in generative AI, machine learning, and deep learning techniques and identify opportunities to integrate them into our products and services. Optimizing existing generative AI models for improved performance, scalability, and efficiency. Ensure data quality and accuracy Leading the design and development of prompt engineering strategies and techniques to optimize the performance and output of our GenAI models. Implementing cutting-edge NLP techniques and prompt engineering methodologies to enhance the capabilities and efficiency of our GenAI models. Determining the most effective prompt generation processes and approaches to drive innovation and excellence in the field of AI technology, collaborating with AI researchers and developers Experience working with cloud based platforms (example: AWS, Azure or related) Strong problem-solving and analytical skills Proficiency in handling various data formats and sources through Omni Channel for Speech and voice applications, part of conversational AI Prior statistical modelling experience

Demonstrable experience with deep learning algorithms and neural networks Developing clear and concise documentation, including technical specifications, user guides, and presentations, to communicate complex AI concepts to both technical and non-technical stakeholders. Contributing to the establishment of best practices and standards for generative AI development within the organization. Work on functional design, process design (including scenario design, flow mapping), prototyping, testing, training, and defining support procedures, in collaboration with an advanced engineering team and executive leadership Articulate and document the solutions architecture and lessons learned for each exploration and accelerated incubation Manage a team in conducting assessments of the AI and automation market and competitor landscape Serve as liaison between stakeholders and project teams, delivering feedback and enabling team members to make necessary changes in product performance or presentation

Six or more years of experience in applying AI to practical and comprehensive technology solutions

Must have solid experience developing and implementing generative AI models, with a strong understanding of deep learning techniques such as GPT, VAE, and GANs.

Must be proficient in Python and have experience with machine learning libraries and frameworks such as TensorFlow, PyTorch, or Keras. Must have strong knowledge of data structures, algorithms, and software engineering principles.

Must be familiar with cloud-based platforms and services, such as AWS, Google Cloud Platform, or Azure.

Need to have experience with ML, deep learning, TensorFlow, Python, Natural Language Processing (NLP) techniques and tools, such as SpaCy, NLTK, or Hugging Face.

Must be familiar with data visualization tools and libraries, such as Matplotlib, Seaborn, or Plotly.

Need to have knowledge of software development methodologies, such as Agile or Scrum. Possess excellent problem-solving skills, with the ability to think critically and creatively to develop innovative AI solutions.

Experience in program leadership, governance, and change enablement Knowledge of basic algorithms, object-oriented and functional design principles, and best-practice patterns

Experience in REST API development, NoSQL database design, and RDBMS design and optimizations

Preferred skills and qualifications:

Must have a degree in Computer Science, Artificial Intelligence, Machine Learning, or a related field. A Ph.D. is highly desirable Experience with innovation accelerators Experience with cloud environments Strong communication skills, with the ability to effectively convey complex technical concepts to a diverse audience