Advanced AI Solution Architect

Role: Advanced AI Solutions Architect Location: Preferred – Phoenix, AZ Secondary Locations: Bay Area, CA / Charlotte, NC (Relocation Required) Rate: Competitive Hourly Rate Position Summary: We are seeking an experienced and hands-on AI Architect to lead the transformation of our intelligent digital assistant by embedding cutting-edge generative AI technologies. The successful candidate will architect and implement flexible, platform-independent solutions to elevate conversational and automation capabilities across our ecosystem. Core Qualifications Technical Skills: Proficient in Java and experienced in building robust backend systems with API integrations. Hands-on expertise with leading AI/ML frameworks (e.g., TensorFlow, PyTorch, Hugging Face). Comfortable working with containerized environments such as OpenShift or similar orchestration platforms. Generative AI Knowledge: Demonstrated success in architecting and deploying generative AI systems (e.g., LLM-based applications). Understanding of prompt design, fine-tuning, and training large-scale language models. Architecture & Engineering: Capable of designing scalable, resilient, and secure AI-driven solutions. Familiarity with enterprise-grade standards including governance, compliance, and model explainability. Cloud & DevOps Proficiency: Hands-on experience with CI/CD pipelines, Kubernetes, and container management. Knowledge of hybrid deployments across cloud and on-prem infrastructure. Soft Skills: Problem-solver with a proactive and practical approach. Strong communication skills and ability to engage both technical teams and business stakeholders. Key Responsibilities 1. Solution Architecture: Lead the design of a comprehensive AI-powered conversational platform enhancement. Ensure solution flexibility and compatibility across various AI models and infrastructure providers. Provide technical direction to engineers implementing the solution. 2. AI Model Integration: Select, adapt, and deploy generative models for dialogue enhancement, summarization, and content generation. Fine-tune and optimize models for real-time enterprise use cases. 3. Platform & Infrastructure Enablement: Maintain high system performance and uptime via seamless integration of backend services and APIs. Build CI/CD pipelines to automate the deployment and lifecycle management of AI services. 4. Technical Development: Stay directly involved in coding, model training, prototyping, and testing of AI capabilities. Partner with cross-functional teams including engineering, data science, and operations. Implement monitoring and diagnostics for AI model and system performance. 5. Cross-Team Collaboration: Work with product leadership and stakeholders to align AI capabilities with business goals. Promote knowledge-sharing, maintain technical documentation, and foster team learning. Preferred Experience Background in conversational platform technologies (e.g., Dialogflow or similar). Exposure to a variety of generative AI solutions, both open and proprietary. Knowledge in natural language processing and conversational AI stacks. Experience modernizing legacy systems into containerized, cloud-native applications.