VP, AI Engineering & Agent Platforms

Opportunity Overview:

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.

What You'll Do:

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.

What you’ll need:

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

Leadership Characteristics

The ideal candidate is:

A platform builder who thinks in systems, sca…