What are the responsibilities and job description for the Senior AI Architect position at Purple Drive?
Location: [US Hartford]
Experience Level: Senior / Leadership Role
Role Overview
We are seeking a Senior AI Architect to lead the design, development, and governance of cutting-edge AI solutions. This role requires both hands-on technical expertise and strategic leadership-driving innovation while ensuring compliance, security, and scalability across our AI ecosystem.
Key Responsibilities
AI Leadership & Strategy:
Lead our end-to-end AI development-balancing hands-on model design and implementation with guiding and mentoring the broader AI engineering and research teams.
Architecture, Design, and Deployment:
Design, build, and deploy production-grade machine learning models-including LLMs-on the Google Cloud Platform (Vertex AI) using Python and related frameworks.
Collaboration & Ecosystem Management:
Partner closely with internal AI teams, Google, and other technology vendors to sustain momentum, drive innovation, and align with evolving best practices.
Governance, Security, and AIRB Compliance:
Own and execute AI governance processes, including AI Risk Board (AIRB) reviews, data security, compliance, and ethical AI considerations across all AI initiatives.
Model Development & Evaluation:
Design and implement models for Conversational AI, leveraging Google CCAI/CES components. Lead model evaluation using robust Eval frameworks and metrics to ensure reliability, accuracy, and fairness.
Advanced Architectures:
Apply agentic architectures and Retrieval Augmented Generation (RAG) to build intelligent, context-aware AI systems. Experience with Parameter Efficient Fine-Tuning (PEFT) is a plus.
Performance & Scalability:
Optimize and fine-tune models for performance, efficiency, scalability, and accuracy across production workloads.
Cross-Functional Collaboration:
Work with business stakeholders and engineering teams to translate complex business problems into scalable and efficient AI-driven solutions.
Continuous Innovation:
Stay ahead of emerging trends in AI/ML, LLMs, and MLOps to continuously enhance solution quality and team capability.
Customer & Partner Engagement:
Collaborate directly with customer technical experts and partners (e.g., Google) to design solutions that meet business goals and compliance requirements, demonstrating technical and business maturity.
Qualifications
Advanced hands-on experience in Machine Learning, LLMs, and MLOps.
Proven expertise in Google Vertex AI, Python, and Google CCAI/CES platforms.
Deep understanding of AI governance, AIRB, security, and responsible AI principles.
Experience in model evaluation frameworks, agentic architectures, and RAG pipelines.
Strong communication and collaboration skills for engaging with cross-functional teams, vendors, and stakeholders.
Demonstrated ability to balance innovation with operational rigor in production-grade AI environments.