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

Required Skills And Qualifications

• 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, GCP, 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