Location: Chicago, IL – Remote
Exp: 15+ years (LinkedIn Mandatory)
Job Description:
We are seeking an experienced Product Manager – AI to lead the end-to-end lifecycle of AI-powered products within a rapidly growing enterprise AI platform. This platform delivers generative and agentic AI capabilities through conversational assistants, intelligent workflows, knowledge retrieval systems, content generation tools, and shared AI services.
The ideal candidate will combine strong product management expertise with practical fluency in modern AI technologies, including LLMs, agents, RAG architectures, and AI evaluation frameworks. This is a highly collaborative role working across Product, Engineering, Design, Security, and Business stakeholders to build trusted, scalable, and impactful AI solutions.
Required Qualifications
- Proven Product Management experience delivering technical, platform, SaaS, AI/ML, or data-intensive products.
- Strong understanding of modern AI technologies including:
- Large Language Models (LLMs)
- Agent-based systems
- Retrieval-Augmented Generation (RAG)
- AI evaluation and monitoring
- Experience translating complex business challenges into product roadmaps and successful product launches.
- Strong cross-functional leadership and stakeholder management skills.
- Experience working within enterprise security, governance, compliance, and Responsible AI frameworks.
Key Responsibilities
Product Strategy & Ownership
- Own the full product lifecycle from discovery through launch and continuous iteration.
- Define and manage product roadmaps aligned with broader platform objectives.
- Conduct user research and stakeholder interviews to identify high-impact opportunities.
- Translate ambiguous business needs into clear product requirements and delivery plans.
- Convert recurring delivery patterns into reusable, scalable product capabilities.
AI Product Design & Platform Integration
- Partner with Engineering and Design teams to deliver AI products within an enterprise platform architecture.
- Drive product decisions related to:
- Multi-agent orchestration
- RAG and knowledge retrieval services
- Shared AI skills and reusable components
- Model selection and orchestration
- Conversational and generative user experiences
- Contribute to platform standards around:
- Prompt engineering and agent design
- AI quality, evaluation, and reliability
- Responsible AI, governance, and safety
- Human-in-the-loop workflows and escalation models
Delivery & Execution
- Collaborate with delivery teams to understand real-world workflows and user needs.
- Prioritize product backlogs and guide investment decisions.
- Drive improvements in AI quality, latency, scalability, reliability, observability, and cost efficiency.
- Define success metrics and monitor product performance across usage, adoption, and AI workload costs.
- Maintain product documentation and standards.
Stakeholder Management
- Partner with Engineering, Design, Security, Compliance, and business stakeholders.
- Communicate technical and business trade-offs effectively.
- Present product strategy, roadmap, and business impact to leadership teams.
Thanks & Regards,
Harshith Reddy
