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AI / ML Architect
USA
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Job Title: Senior AI Architect

Location: US

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.


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