Solutions Architect - Public Sector

Who are we? Cohere is the leading security-first enterprise AI company. We build cutting-edge foundation AI models and end-to-end products that are designed to solve real-world business problems. We’re training and deploying frontier models for enterprises who are building AI systems. We believe that our work is instrumental to the widespread adoption of AI and we are looking for folks that want to be part of that. We obsess over what we build. Each one of us is responsible for contributing to increasing the capabilities of our models and the value they drive for our customers. Cohere is a team of researchers, engineers, designers, and more, who are all passionate about their craft. We are a global technology company co-headquartered in Toronto and San Francisco, with key offices in London, New York City, Montreal, Seoul, Germany and Paris. Join us! Why this role? In this role as a Solutions Architect at Cohere, you will play a significant role in growing Cohere’s Defence and National Security business. In this dynamic role, you will need to be both a strategic thinker and a hands-on doer. You will take a hands-on approach to building customer demos and proof of concepts that showcase the business value of our platform. As the technical relationship owner, you will collaborate with stakeholders to understand their business objectives and translate those into technical solutions. You will take ownership of the customer narrative, serving as the voice of the customer and acting as a liaison between the customer and our product team. Additionally, you will provide guidance on best practices for using Cohere, identify areas for improvement within the platform, and cultivate technical champions within customer organizations to drive adoption and gather feedback to enhance our products. In this role, you will: - Develop and deliver cutting-edge agentic AI solutions utilizing Cohere’s foundation models and Agentic AI Foundry - North. - Architect scalable, secure, and customizable NLP and generative AI solutions tailored to enterprise customer needs. - Collaborate with customers to understand complex workflows, design pilots, and translate business requirements into technical solutions encompassing model fine-tuning, custom agents, and agent orchestration. - Support deployment and integration of large language models (LLMs) and custom solutions into production environments using Kubernetes, Docker, and cloud infrastructures, ensuring high performance and security. - Lead technical engagements, including deep dives into AI architectures, workshop facilitation, and establishing best practices for agent-based AI systems and model customization. - Work with product development to provide customer feedback on agentic AI capabilities, contribute to product enhancements, and help shape future features. This career opportunity may be a good match for you if you possess: - 5+ years of experience in AI/ML solution architecture, with demonstrated expertise in agentic AI, model customization, and deploying tailored AI models in enterprise contexts. - Strong hands-on skills with Python, Jupyter Notebooks, and cloud-native deployment frameworks such as Kubernetes, Docker, Cloud managed AI services like AWS Sagemaker, Bedrock, or Azure AI Foundry or Google Vertex AI. - Experience in designing and deploying “agentified” AI workflows, that involve multiple interconnected models or agents, to solve business challenges. - Hands-on experience building on agent orchestration frameworks like Cohere North and deploying custom agents to production. - Familiarity with model fine-tuning methodologies, and the development of AI agents optimized for specific workflows and enterprise needs. - In-depth understanding of the strengths, weaknesses, and operational considerations of generative LLMs, with experience in customizing and orchestrating these models. - Excellent communication skills to articulate complex AI architectures to both technical stakeholders and executive audiences. - Nice to have: Background in building and managing scalable AI/ML ecosystems, with knowledge of multi-cloud deployment strategies. - Nice to have: Familiarity with security standards for deploying agent-based AI solutions, including data privacy, model safety, and access controls. - Nice to have: Experience working in a startup-like context. Cohere is committed to fair and transparent pay practices. The salary range listed for this role reflects the expected base compensation. Actual compensation offered will be determined by factors such as location, level, job-related knowledge, skills, education, and experience. For candidates in Ottawa, the Compensation Range is: 265,000 - 315,000 Full-Time Employees at Cohere enjoy these Perks: - A weekly lunch stipend of $75/£75 or equivalent in your local currency for lunch. - Full health and dental benefits, including a separate budget for mental health. - RRSP matching, 401K, Pension Scheme. - 100% P

This career opportunity may be a good match for you if you possess: - 5+ years of experience in AI/ML solution architecture, with demonstrated expertise in agentic AI, model customization, and deploying tailored AI models in enterprise contexts. - Strong hands-on skills with Python, Jupyter Notebooks, and cloud-native deployment frameworks such as Kubernetes, Docker, Cloud managed AI services like AWS Sagemaker, Bedrock, or Azure AI Foundry or Google Vertex AI. - Experience in designing and deploying “agentified” AI workflows, that involve multiple interconnected models or agents, to solve business challenges. - Hands-on experience building on agent orchestration frameworks like Cohere North and deploying custom agents to production. - Familiarity with model fine-tuning methodologies, and the development of AI agents optimized for specific workflows and enterprise needs. - In-depth understanding of the strengths, weaknesses, and operational considerations of generative LLMs, with experience in customizing and orchestrating these models. - Excellent communication skills to articulate complex AI architectures to both technical stakeholders and executive audiences. - Nice to have: Background in building and managing scalable AI/ML ecosystems, with knowledge of multi-cloud deployment strategies. - Nice to have: Familiarity with security standards for deploying agent-based AI solutions, including data privacy, model safety, and access controls. - Nice to have: Experience working in a startup-like context.

In this role as a Solutions Architect at Cohere, you will play a significant role in growing Cohere’s Defence and National Security business. You will take a hands-on approach to building customer demos and proof of concepts that showcase the business value of our platform. As the technical relationship owner, you will collaborate with stakeholders to understand their business objectives and translate those into technical solutions. You will take ownership of the customer narrative, serving as the voice of the customer and acting as a liaison between the customer and our product team. Additionally, you will provide guidance on best practices for using Cohere, identify areas for improvement within the platform, and cultivate technical champions within customer organizations to drive adoption and gather feedback to enhance our products. This role includes: - Develop and deliver cutting-edge agentic AI solutions utilizing Cohere’s foundation models and Agentic AI Foundry - North. - Architect scalable, secure, and customizable NLP and generative AI solutions tailored to enterprise customer needs. - Collaborate with customers to understand complex workflows, design pilots, and translate business requirements into technical solutions encompassing model fine-tuning, custom agents, and agent orchestration. - Support deployment and integration of large language models (LLMs) and custom solutions into production environments using Kubernetes, Docker, and cloud infrastructures, ensuring high performance and security. - Lead technical engagements, including deep dives into AI architectures, workshop facilitation, and establishing best practices for agent-based AI systems and model customization. - Work with product development to provide customer feedback on agentic AI capabilities, contribute to product enhancements, and help shape future features.