Zencore - Principal Architect, AI/ML
Requirements
• Serve as Zencore’s senior-most technical authority on the practical application of advanced artificial intelligence and machine learning. • Partner with the sales and business development teams in a pre-sales capacity to scope opportunities, design solutions for proposals, and act as the senior technical voice in client pitches. • Lead the architecture and design of sophisticated, secure, and scalable AI solutions for our clients, moving beyond standard API integrations to create genuine competitive advantages. • Collaborate closely with Cloud & Data Architects to guarantee the design and deployment of comprehensive client solutions. • Address the growing European demand for private, data-sovereign AI by designing systems that meet strict GDPR and data privacy requirements. Strive for model explainability and bias mitigation, ensuring solutions adhere to ethical standards and European safety guardrails. • Architect solutions for hosting, fine-tuning, and optimizing both proprietary (e.g., Gemini, Claude) and open-source (e.g., Llama, Mistral) models on hyperscaler platforms. • Lead clients in selecting optimal cloud-native technologies, prioritizing Google Cloud solutions for deploying and scaling production-grade agentic systems. • Guide and mentor customers and Zencore's engineering teams on advanced topics, establishing best practices for high-performance training (PyTorch, JAX, TPUs), efficient model serving (vLLM), and complex agentic systems (LangGraph, Langchain, Google ADK). • Devise the financial architecture of AI solutions by performing ROI analysis and implementing cost-optimization strategies to ensure large-scale deployments remain economically sustainable for customers. • Act as an external thought leader, contributing to the Zencore brand through blog posts, conference presentations, and community engagement. • Act as a "player-coach," providing hands-on leadership and fostering a culture of deep technical excellence in AI/ML. • Master’s degree in Computer Science, natural sciences, mathematics, or a related technical field, or equivalent practical experience in designing and delivering high-scale AI/ML systems. • Extensive experience in a senior or principal architect role with a proven track record of designing and delivering complex, production-grade machine learning systems that have created measurable business value. • Deep, hands-on architectural experience with at least one major cloud platform (GCP, AWS, or Azure) is required. • Direct, hands-on experience with Google Cloud (Vertex AI, GKE, TPUs) is a significant plus. • Proven expertise in LLM optimization, including techniques for quantization, pruning, efficient fine-tuning (e.g., LoRA), and high-performance serving (e.g., vLLM, TensorRT-LLM). • Hands-on experience with high-performance ML frameworks (e.g., JAX, PyTorch/XLA) for training or fine-tuning large-scale models. • Expertise in designing and deploying agentic workflows using both code-centric (e.g., LangGraph, LangChain, Google ADK) and low-code (e.g., Vertex AI Agent Builder, LangSmith Agent Builder) paradigms. • A strong understanding of the architectural patterns required for building secure, private, and data-sovereign AI solutions. • Experience with LLM observability and evaluation frameworks (e.g., LangSmith, LangFuse, Vertex AI Evaluation). • Exceptional communication and stakeholder management skills, with the ability to articulate complex technical concepts and their business value to both technical and non-technical audiences. • A passion for mentoring and a drive for continuous learning in the fast-evolving AI landscape.
Responsibilities
• Serve as Zencore’s senior-most technical authority on the practical application of advanced artificial intelligence and machine learning. • Partner with the sales and business development teams in a pre-sales capacity to scope opportunities, design solutions for proposals, and act as the senior technical voice in client pitches. • Lead the architecture and design of sophisticated, secure, and scalable AI solutions for our clients, moving beyond standard API integrations to create genuine competitive advantages. • Collaborate closely with Cloud & Data Architects to guarantee the design and deployment of comprehensive client solutions. • Address the growing European demand for private, data-sovereign AI by designing systems that meet strict GDPR and data privacy requirements. Strive for model explainability and bias mitigation, ensuring solutions adhere to ethical standards and European safety guardrails. • Architect solutions for hosting, fine-tuning, and optimizing both proprietary (e.g., Gemini, Claude) and open-source (e.g., Llama, Mistral) models on hyperscaler platforms. • Lead clients in selecting optimal cloud-native technologies, prioritizing Google Cloud solutions for deploying and scaling production-grade agentic systems. • Guide and mentor customers and Zencore's engineering teams on advanced topics, establishing best practices for high-performance training (PyTorch, JAX, TPUs), efficient model serving (vLLM), and complex agentic systems (LangGraph, Langchain, Google ADK). • Devise the financial architecture of AI solutions by performing ROI analysis and implementing cost-optimization strategies to ensure large-scale deployments remain economically sustainable for customers. • Act as an external thought leader, contributing to the Zencore brand through blog posts, conference presentations, and community engagement. • Act as a "player-coach," providing hands-on leadership and fostering a culture of deep technical excellence in AI/ML. • Master’s degree in Computer Science, natural sciences, mathematics, or a related technical field, or equivalent practical experience in designing and delivering high-scale AI/ML systems. • Extensive experience in a senior or principal architect role with a proven track record of designing and delivering complex, production-grade machine learning systems that have created measurable business value. • Deep, hands-on architectural experience with at least one major cloud platform (GCP, AWS, or Azure) is required. • Direct, hands-on experience with Google Cloud (Vertex AI, GKE, TPUs) is a significant plus. • Proven expertise in LLM optimization, including techniques for quantization, pruning, efficient fine-tuning (e.g., LoRA), and high-performance serving (e.g., vLLM, TensorRT-LLM). • Hands-on experience with high-performance ML frameworks (e.g., JAX, PyTorch/XLA) for training or fine-tuning large-scale models. • Expertise in designing and deploying agentic workflows using both code-centric (e.g., LangGraph, LangChain, Google ADK) and low-code (e.g., Vertex AI Agent Builder, LangSmith Agent Builder) paradigms. • A strong understanding of the architectural patterns required for building secure, private, and data-sovereign AI solutions. • Experience with LLM observability and evaluation frameworks (e.g., LangSmith, LangFuse, Vertex AI Evaluation). • Exceptional communication and stakeholder management skills, with the ability to articulate complex technical concepts and their business value to both technical and non-technical audiences. • A passion for mentoring and a drive for continuous learning in the fast-evolving AI landscape. • We are a fully remote company and offer competitive compensation and benefits.
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