Principal Architect, AI/ML

Accountabilities:

• Lead the architecture, design, and delivery of sophisticated AI and machine learning solutions that address complex business and technical challenges across enterprise environments.


• Serve as a senior technical advisor during pre-sales engagements by helping scope opportunities, define solution strategies, and support technical presentations and client discussions.


• Design scalable, secure, and data-sovereign AI architectures aligned with regulatory requirements, privacy standards, ethical AI principles, and model explainability best practices.


• Architect and optimize AI platforms for hosting, fine-tuning, serving, and scaling both proprietary and open-source large language models across hyperscaler cloud environments.


• Guide engineering teams and clients on advanced AI/ML topics including high-performance model training, LLM optimization, inference efficiency, observability, and agentic workflows.


• Collaborate closely with cloud, infrastructure, and data architecture teams to ensure seamless integration of AI solutions into broader enterprise ecosystems.


• Lead the implementation of modern MLOps practices, deployment pipelines, monitoring frameworks, and AI governance standards for production-grade systems.


• Evaluate and recommend optimal cloud-native technologies, frameworks, and tooling to support scalable and cost-efficient AI deployments.


• Perform ROI analysis and cost optimization planning to ensure the long-term sustainability and operational efficiency of AI initiatives.


• Mentor engineering teams, promote technical excellence, and contribute to thought leadership through community engagement, technical publications, and industry presentations.

Requirements

• Master’s degree in Computer Science, Mathematics, Engineering, Natural Sciences, or a related technical discipline, or equivalent practical experience delivering large-scale AI/ML systems.


• Extensive experience in senior or principal architecture roles with a proven record of designing and deploying production-grade AI and machine learning solutions.


• Deep expertise with at least one major cloud platform such as Google Cloud Platform, AWS, or Microsoft Azure.


• Strong hands-on experience with Google Cloud AI services, including technologies such as Vertex AI, GKE, and TPUs, is highly desirable.


• Proven expertise in large language model optimization techniques including quantization, pruning, LoRA fine-tuning, efficient inference, and model serving frameworks such as vLLM or TensorRT-LLM.


• Advanced knowledge of machine learning frameworks and high-performance training environments including PyTorch, JAX, PyTorch/XLA, or equivalent technologies.


• Experience designing and deploying agentic AI systems using frameworks such as LangGraph, LangChain, Google ADK, Vertex AI Agent Builder, or similar orchestration tools.


• Strong understanding of AI observability, evaluation, governance, and monitoring frameworks including LangSmith, LangFuse, Vertex AI Evaluation, or related tools.


• Expertise designing secure, private, and data-sovereign AI systems that comply with regulatory and privacy requirements.


• Excellent communication, stakeholder management, and consulting skills with the ability to explain complex technical concepts to both technical and non-technical audiences.


• Demonstrated leadership, mentoring, and collaboration skills with a passion for innovation and continuous learning in the evolving AI landscape.

• Fully remote work environment with flexibility for candidates based in the EU or United Kingdom.


• Competitive compensation package aligned with senior-level technical expertise and industry impact.


• Opportunity to work on cutting-edge AI, ML, and cloud-native technologies with leading innovative organizations.


• Exposure to high-impact enterprise transformation projects involving large-scale AI adoption and modernization initiatives.


• Collaborative and technically advanced engineering culture focused on innovation, learning, and mentorship.


• Opportunities for professional growth, technical leadership, and thought leadership within the AI community.


• Flexible work structure designed to support autonomy, productivity, and work-life balance.


• Inclusive and diverse work environment that values collaboration, creativity, and continuous improvement.


• Ability to contribute directly to strategic AI initiatives shaping the future of enterprise technology solutions.

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