Applied AI Engineer – Agentic Workflows
Who are we? Our mission is to scale intelligence to serve humanity.
What this role actually needs.
Who are we? Our mission is to scale intelligence to serve humanity. Responsibilities: - Work closely with enterprise customers to translate high-value, ambiguous business problems into well-framed agentic problems with clear success criteria and evaluation methodologies. - Provide technical leadership across the full development and evaluation lifecycle, including post-deployment iteration, for agentic workflows. - Contribute to shared frameworks and patterns that enable consistent delivery across customers. - Lead the design, build, and delivery of LLM-powered agents that reason, plan, and act across tools and data sources with enterprise-grade reliability and performance. - Balance rapid iteration with enterprise requirements, evolving prototypes into stable, reusable solutions. - Define and apply evaluation and quality standards to measure success, failures, and regressions. Requirements: - Define and apply evaluation and quality standards to measure success, failures, and regressions. - Debug real-world agent behavior and systematically improve prompts, workflows, tools, and guardrails. - Mentor engineers across distributed teams. - Drive clarity in ambiguous situations, build alignment, and raise engineering quality across the organization. Company context: Cohere builds enterprise AI models, tooling, and infrastructure with meaningful technical hiring across Canada and the United States.
Day-to-day expectations
Cohere lists these responsibilities for the Applied AI Engineer – Agentic Workflows role.
- Work closely with enterprise customers to translate high-value, ambiguous business problems into well-framed agentic problems with clear success criteria and evaluation methodologies.
- Provide technical leadership across the full development and evaluation lifecycle, including post-deployment iteration, for agentic workflows.
- Contribute to shared frameworks and patterns that enable consistent delivery across customers.
- Lead the design, build, and delivery of LLM-powered agents that reason, plan, and act across tools and data sources with enterprise-grade reliability and performance.
- Balance rapid iteration with enterprise requirements, evolving prototypes into stable, reusable solutions.
- Define and apply evaluation and quality standards to measure success, failures, and regressions.
What a strong candidate brings
These requirements are extracted from the source listing and normalized for UpJobz readers.
- Define and apply evaluation and quality standards to measure success, failures, and regressions.
- Debug real-world agent behavior and systematically improve prompts, workflows, tools, and guardrails.
- Mentor engineers across distributed teams.
- Drive clarity in ambiguous situations, build alignment, and raise engineering quality across the organization.
Why this listing is more than a copied job post.
Applied AI Engineer – Agentic Workflows is framed against UpJobz source checks, country scope, compensation visibility, and work-authorization signals so candidates can make a faster go/no-go decision.
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Source: jobs.ashbyhq.com · Source ID: 1fa01a03-9253-4f62-8f10-0fe368b38cb9 · Confidence: 94/100 · Last checked: May 7, 2026
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