VP, AI Engineering & Agent Platforms

VP, AI Engineering & Agent Platforms

United States

Reporting to the Chief Digital & Technology Officer, the Vice President of AI Engineering & Agent Platforms will lead the teams responsible for AI platform engineering, agent platforms, agent runtime systems, skills and prompt lifecycle management and framework, AI infrastructure, MLOps/LLMOps, and forward deployed AI engineering.

This role partners closely with the Chief Data & AI Officer, who owns Cohere's AI strategy, model development, evaluation frameworks, prompt design and governance, skills requirements and behavior, knowledge management frameworks, and data science functions. The VP of AI Engineering & Agent Platforms is responsible for operationalizing, scaling, deploying, and running those capabilities across Cohere's products and customer environments.

This leader will build the platforms, engineering systems, and deployment capabilities that enable Cohere to rapidly deliver AI-powered solutions while maintaining the reliability, security, and compliance required in healthcare.

Build and Scale Our AI Platform

Lead the engineering organization responsible for the foundational platforms and services that power Cohere's AI ecosystem.

Responsibilities include:

• AI infrastructure and runtime platforms
• Agent orchestration, workflow, and execution services
• Document processing and knowledge ingestion pipelines
• MLOps and LLMOps capabilities
• AI observability, monitoring, and reliability
• Partnership with core teams to build AI native Developer platforms and engineering productivity tools
• Build and evolve Cohere's enterprise agent platform, enabling teams to rapidly develop, evaluate, deploy, govern, and operate AI agents at scale.

Lead Agent Engineering

Build the frameworks, services, and reusable capabilities that enable teams to rapidly develop, test, deploy, and operate secure, observable, and production-ready AI-powered solutions.

Areas of focus include:

• Agent architectures, orchestration, and runtime frameworks
• Multi-agent systems and workflow automation
• Skills management and reusable action frameworks
• Evaluation, testing, and agent observability infrastructure
• Human-in-the-loop and supervised AI workflows
• Enterprise integrations and action surfaces
• Partnership in skills design with data science

Design and scale the engineering systems used to build, manage, deploy, and govern reusable agent skills across healthcare workflows.

Lead Prompt and Skills Lifecycle Operations

Establish the platforms and operational capabilities required to manage AI behavior at scale.

Responsibilities include:

• Prompt lifecycle management
• Prompt deployment and versioning
• Prompt testing infrastructure
• Skills deployment and governance
• Agent configuration management
• AI release management and rollback capabilities

Scale a Forward Deployed AI Engineering Organization

Lead a team of customer-facing engineers responsible for deploying and operationalizing Cohere's AI solutions within customer environments.

This organization partners closely with customers to:

• Implement AI-powered workflows
• Integrate with enterprise systems
• Accelerate adoption and value realization
• Establish repeatable deployment patterns that enable scale
• Support complex customer implementations and transformations

Drive Operational Excellence

Establish engineering best practices, platform standards, and operational processes that allow Cohere to scale AI safely and efficiently across customers, products, and healthcare workflows.

Partner closely with Product, Clinical Operations, Customer Success, Security, and the Chief Data & AI Officer's organization to ensure AI capabilities move efficiently from concept to production.

Must-Haves

• 15+ years of software engineering experience, including significant leadership responsibility
• Experience leading large-scale platform, infrastructure, or AI engineering organizations
• Proven track record building and operating cloud-native, data-rich products and platforms
• Experience deploying AI-powered applications into production environments
• Experience with AWS or other modern cloud-native technologies
• Healthcare or other highly regulated industry experience
• Deep understanding of distributed systems, platform engineering, and modern software architecture
• Experience building and leading high-performing engineering teams

Nice-to-Haves

• Experience with generative AI, agentic systems, and AI platform development
• Experience building agent platforms, skills frameworks, or AI developer platforms
• Experience with MLOps, LLMOps, AI infrastructure, and developer tooling
• Experience working directly with enterprise customers on complex technical implementations
• Track record developing data-rich applications leveraging structured and unstructured data
• Experience leading customer-facing engineering or forward deployed engineering organizations

The ideal candidate is:

• A platform builder who thinks in systems, scale, and reusable capabilities
• Passionate about turning innovation into reliable,…