Position Overview

We are seeking a technically knowledgeable AI Agent Product Owner to lead the development, implementation, and continuous improvement of AI-powered agents within a Microsoft Azure environment.

This individual will work closely with engineering, cloud infrastructure, AI/ML teams, and business stakeholders to identify opportunities for AI automation, translate business requirements into technical solutions, and drive the delivery of scalable AI agent capabilities.

The ideal candidate will have a strong product ownership background, experience working with cloud-based technologies, and an understanding of generative AI, large language models (LLMs), and agentic AI architectures.

Key Responsibilities

Product Ownership & Strategy

• Own and manage the product roadmap for AI agents and intelligent automation solutions.
• Partner with business stakeholders to identify opportunities to leverage AI agents to streamline workflows, improve operational efficiency, and automate business processes.
• Translate business needs into product requirements, user stories, acceptance criteria, and technical deliverables.
• Manage and prioritize the product backlog based on business value, technical feasibility, and organizational priorities.
• Define product success metrics and evaluate the effectiveness of deployed AI agents.
• Drive AI agent initiatives from initial discovery and proof of concept through production deployment and ongoing optimization.

AI Agent Development & Implementation

• Collaborate with AI engineers and developers to design and implement AI agents capable of executing tasks, retrieving information, and automating workflows.
• Understand agentic AI concepts, including autonomous task execution, tool calling, orchestration, reasoning, and multi-agent workflows.
• Work with engineering teams to integrate large language models into enterprise applications and business processes.
• Support the development of AI agents using technologies such as Azure AI Foundry, Azure OpenAI, and relevant agent orchestration frameworks.
• Partner with technical teams to define integrations between AI agents, enterprise applications, APIs, and internal data sources.
• Establish requirements for AI agent performance, reliability, accuracy, security, and scalability.
• Coordinate testing and validation of AI agents to ensure solutions meet business expectations.

Microsoft Azure Environment

• Work closely with cloud engineering teams to deliver AI solutions within the Microsoft Azure ecosystem.
• Understand Azure AI services and their application in building enterprise AI solutions.
• Collaborate with engineers leveraging Azure Functions, Azure Logic Apps, Azure AI Search, Azure Storage, and API Management.
• Support integration of AI agents with enterprise systems and cloud-based applications.
• Partner with engineering and security teams to ensure solutions follow cloud governance, data privacy, and security standards.
• Understand how AI agents interact with APIs, databases, and enterprise data environments.

Agile Delivery & Cross-Functional Collaboration

• Serve as the primary liaison between business stakeholders, AI development teams, and cloud engineering resources.
• Lead backlog refinement, sprint planning, product demonstrations, and acceptance testing.
• Work within Agile/Scrum environments to ensure consistent delivery of product enhancements.
• Coordinate dependencies across engineering, data, infrastructure, and security teams.
• Communicate project progress, technical challenges, risks, and milestones to stakeholders.
• Balance strategic product priorities with hands-on execution and day-to-day delivery management.

Required Qualifications

• 4+ years of experience in Product Ownership, Technical Product Management, or a similar technology-focused role.
• Experience delivering cloud-based applications or enterprise technology solutions.
• Working knowledge of Microsoft Azure and cloud-native application architectures.
• Experience working on AI, generative AI, machine learning, or intelligent automation initiatives.
• Understanding of AI agents, LLMs, prompt engineering, and retrieval-augmented generation (RAG).
• Experience managing technical product backlogs, developing user stories, and defining acceptance criteria.
• Ability to work closely with software engineers and understand APIs, system integrations, and application development lifecycles.
• Familiarity with Agile methodologies, Scrum practices, and CI/CD processes.
• Strong stakeholder management skills with the ability to translate complex technical concepts into business language.
• Experience managing products from initial requirements through implementation and production support.

Preferred Qualifications

• Hands-on exposure to Azure AI Foundry, Azure OpenAI, or Microsoft Copilot Studio.
• Experience with agent orchestration frameworks such as Semantic Kernel, AutoGen, or LangChain.
• Familiarity with Azure AI Search, vector databases, and RAG architectures.
• Experience implementing enterprise AI agents or multi-agent solutions.
• Understanding of Microsoft Entra ID, Azure security, and identity management.
• Familiarity with Python, REST APIs, and cloud-based integration patterns.
• Experience with Azure DevOps, Jira, or similar product management tools.
• Experience implementing AI governance, responsible AI practices, and model evaluation frameworks.
• Background in enterprise automation, digital transformation, or platform engineering.

Ideal Candidate Profile

The ideal candidate is a technically oriented Product Owner who understands how AI agents are developed and deployed within Azure, while also possessing the business acumen to identify valuable use cases and drive product adoption.

This individual does not need to be a hands-on AI developer but should be comfortable discussing AI architectures, agent orchestration, cloud services, and technical integrations with engineering teams.

They should be capable of bringing structure to ambiguous initiatives, prioritizing competing business needs, and driving AI products from concept to production.

Key areas of expertise:

• AI Agents & Generative AI
• Microsoft Azure Cloud Environment
• Technical Product Ownership
• AI Automation & Workflow Orchestration
• Enterprise Application Integration
• Agile Product Delivery
• Cross-Functional Stakeholder Management