Solutions Architect - Public Sector
Designs and deploys secure, customized agentic AI and generative AI solutions for enterprise and public-sector customers. The role requires 5+ years of AI/ML solution architecture experience, hands-on cloud-native deployment skills, and strong customer-facing communication.
About the job
Responsibilities
- Develop and deliver agentic AI solutions using Cohere’s foundation models and Agentic AI Foundry - North.
- Architect scalable, secure, and customizable NLP and generative AI solutions for enterprise customers.
- Understand complex customer workflows, design pilots, and translate business requirements into technical solutions involving model fine-tuning, custom agents, and agent orchestration.
- Support deployment and integration of large language models and custom solutions into production using Kubernetes, Docker, and cloud infrastructure.
- Lead technical engagements, including AI architecture deep dives, workshops, and best-practice development for agent-based AI systems and model customization.
- Provide customer feedback to product development and contribute to product enhancements and future features.
Requirements
- 5+ years of experience in AI/ML solution architecture.
- Expertise in agentic AI, model customization, and deploying tailored AI models in enterprise environments.
- Hands-on experience with Python, Jupyter Notebooks, Kubernetes, Docker, and cloud-native deployment frameworks.
- Experience with cloud-managed AI services such as AWS SageMaker, Amazon Bedrock, Azure AI Foundry, or Google Vertex AI.
- Experience designing and deploying agent-based AI workflows involving multiple interconnected models or agents.
- Hands-on experience with agent orchestration frameworks such as Cohere North and deploying custom agents to production.
- Familiarity with model fine-tuning methodologies and developing AI agents for specific workflows.
- Strong understanding of the strengths, weaknesses, and operational considerations of generative large language models.
- Excellent communication skills for explaining complex AI architectures to technical and executive audiences.
Nice-to-haves
- Experience building and managing scalable AI/ML ecosystems, including multi-cloud deployment strategies.
- Familiarity with security standards for agent-based AI solutions, including data privacy, model safety, and access controls.
- Experience working in a startup-like context.
Compensation and Benefits
- Ottawa base compensation range: 265,000 - 315,000 CAD annually.
- Weekly lunch stipend of $75/£75 or local-currency equivalent.
- Full health and dental benefits, including a separate mental-health budget.
- RRSP matching, 401K, and pension scheme.
- Up to six months of 100% parental-leave top-up for either parent.
- Annual enrichment benefits for arts and culture, fitness and wellness, quality time, and workspace improvements.
- Education and learning stipend for conferences, courses, and coaching.
- Six weeks of paid vacation.
- Travel budget for remote employees and annual company offsite.
- Coworking benefit and a $500 home-office stipend.
Skills
Python, Jupyter Notebooks, Kubernetes, Docker, Aws Sagemaker, Amazon Bedrock, Azure Ai Foundry, Google Vertex Ai, Cohere North, Model Fine-Tuning, LLMs, Agent Orchestration, Generative AI, NLP, Multi-Cloud Deployment
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