Cohere

Solutions Architect - Defence and National Security

Ottawa · Full-time

No sponsorshipDetected 64 days ago

PythonAWSAzureDockerKubernetesMachine LearningNLPLLMsAgentic AIAI OrchestrationCommunication

About the role

Cohere is the leading security-first enterprise AI company.
Cohere is a team of researchers, engineers, designers, and more, who are all passionate about their craft.
In this role as a Solutions Architect at Cohere, you will play a significant role in growing Cohere's Defence and National Security business.

Develop and deliver cutting-edge agentic AI solutions utilizing Cohere's foundation models and Agentic AI Foundry
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.
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 obsess over what we build.
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.
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.
We strive to create an inclusive work environment for all; we welcome applicants from all backgrounds and are committed to providing equal opportunities.

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.
Experience in designing and deploying "agentified" AI workflows, that involve multiple interconnected models or agents, to solve business challenges.
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.

Familiarity with security standards for deploying agent-based AI solutions, including data privacy, model safety, and access controls.
Experience working in a startup-like context.

6 weeks of paid vacation (30 working days!)
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% Parental Leave top-up for up to 6 months, for either parent.
Arts & culture, fitness/wellness, quality time, and a workspace improvement credit.
Education & learning stipend for conferences, courses, and coaching.
For those not near an office: a co-working benefit so you can work alongside others in your city.
Everyone receives a $500 home office stipend to set up your workspace properly.

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.
Each one of us is responsible for contributing to increasing the capabilities of our models and the value they drive for our customers.
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.
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.

This listing is sourced directly from Cohere's careers page and normalized into a canonical job model.