AI Engineer

Title AI Engineer

Location: Newport Beach

Must have:


7+ years of experience in full-stack development, with a strong focus on Python.


Development Experience deploying Python solutions (e.g., Web Apps, APIs, SPA integrations) to Azure with IaC (e.g., Azure CLI, Azd, Bicep, PowerShell/Bash, Oryx).


Experience building AI/Client applications using LLM, Client technology, using Open AI, Llama or other models.


Experience with Python web frameworks (e.g., Django, Flask).


Solid understanding of object-oriented programming (OOP) principles.


Familiarity with database technologies (e.g. PostgreSQL, Cosmos DB, MongoDB).

Role Overview:
We are seeking a talented and experienced AI Engineer to join our team. In this role, you will be instrumental in developing our next-generation chatbot using AI and LLM technology. You will work closely with a cross-functional team to design, build, and deploy sophisticated AI applications that understand, interpret, and respond to human language in a way that is both meaningful and relevant. The ideal candidate will have a deep understanding of full-stack technology, with a passion for developing scalable, high-performance applications. You will play a key role in the entire application lifecycle, from concept stage to delivery and post-launch support.
Our Tech Stack includes: Python, JavaScript (& based frameworks), Azure, Snowflake, Terraform, Bicep, Azure CLI, CDK, Redis, Docker, Git, Gitlab CI/CD, Database (NoSQL: Cosmos DB, MongoDB, Document DB)

Responsibilities:

Design and Development: Architect, design and develop advanced AI models for our LLM application, focusing on natural language understanding (NLU), natural language processing (NLP), and machine learning (Client) algorithm


Collaboration : Work closely with product managers, UX/UI designers, and software engineers to integrate AI models into our existing apps, ensuring a seamless and intuitive user experience.


Testing : Implement rigorous testing frameworks to evaluate the performance of AI models. Continuously refine and optimize models based on feedback and performance metrics.


Innovation : Stay abreast of the latest developments in AI, LLM, NLP, and Client. Conduct research to explore new methodologies, technologies, and tools and apply them into operations and activities.


Documentation and Knowledge Sharing : Document AI model development processes, architectures, and best practices. Share knowledge and mentor junior team members in AI technologies and methodologies.


Security : Implement responsible AI, security and data protection solutions.


UI/UX: Optimize applications for speed and scalability.