Gen AI Architect - Onsite

Role : Gen AI Architect
Location : Preferred Work Location: Phoenix, AZ
Secondary Work Location(s): Bay Area, CA / Charlotte, NC

We are seeking a hands-on Generative AI Architect to lead the enhancement of our existing virtual assistant, by incorporating state-of-the-art generative AI capabilities. The ideal candidate will design, implement, and optimize solutions that are model, vendor, and platform agnostic.

Required Qualifications
Technical Expertise: Strong programming skills in Java and familiarity with API-driven backend development. Experience with AI/ML frameworks like TensorFlow, PyTorch, Hugging Face, or equivalent. Proficiency in building and deploying applications on OpenShift or other container orchestration platforms.

• Generative AI Experience: Proven experience in designing and deploying generative AI solutions, including LLM-based applications. Understanding of prompt engineering, fine-tuning, and training generative models.
• System Design and Architecture: Ability to design scalable, fault-tolerant, and secure AI systems. Knowledge of data governance, compliance, and model explainability in enterprise environments.
• Cloud and DevOps: Experience with CI/CD pipelines, containerization, and orchestration tools like Kubernetes. Familiarity with hybrid cloud and on-premises systems.
• Soft Skills: Strong problem-solving skills and a hands-on approach to tackling technical challenges. Excellent communication and collaboration skills to influence diverse technical and non-technical stakeholders.

Key Responsibilities

1. Architectural Leadership:
Design and develop an end-to-end architecture for integrating generative AI capabilities into the current virtual assistant.
Ensure solutions are model-agnostic, vendor-neutral, and adaptable across multiple platforms.
Lead and mentor the technical team to implement and optimize the architecture.

2. Generative AI Integration:
Evaluate and select generative AI models and frameworks suitable for conversational AI enhancements.
Build, fine-tune, and integrate generative models for tasks like response generation, summarization, and personalized interactions.
Optimize performance, scalability, and accuracy for real-world use cases.

3. Platform Migration and Scalability:
Ensure seamless integration of backend APIs, maintaining high availability and performance.
Develop a robust CI/CD pipeline for deploying and managing AI models and services on OCP.

4. Technical Implementation:
Stay hands-on with coding, prototyping, and testing AI components.
Collaborate with cross-functional teams, including backend engineers, DevOps, and data scientists, to deliver integrated solutions.
Build monitoring and alerting systems for AI model performance and application reliability.

5. Collaboration and Stakeholder Management:
Work closely with product managers, business stakeholders, and engineers to align technical solutions with business goals.
Provide technical thought leadership, documentation, and knowledge-sharing to support team growth and alignment.

Preferred Qualifications
Experience working with virtual assistant platforms like Google Dialogflow or similar.
Knowledge of multiple generative AI models, including proprietary and open-source solutions.
Understanding of NLP, conversational AI, and related frameworks.
Experience with migrating legacy systems to modern cloud-native architectures.