Lead Edge AI Solutions Product Manager

Manpower San Diego; San Diego (CA); On-site; USD 120,000 - 180,000; Full time

Job summary

Manpower San Diego is seeking a Solutions Product Manager for Edge and Agentic AI to define, develop, and bring to market end-to-end AI solutions across edge devices, compute platforms, software, and cloud services.

You will translate customer requirements into solution architectures, reference implementations, and deployment plans, and collaborate with engineering teams, customers, and partners to integrate AI models, hardware acceleration, security, and lifecycle-management tools for scalable

Qualifications

• Bachelor's degree in Engineering, Information Systems, CS, or related field.
• At least 4 years in Product Management or related experience.
• Strong technical depth in AI and edge deployment.

Responsibilities

• Define, develop, and bring to market end-to-end AI solutions for edge, compute, software, and cloud.
• Translate customer requirements into solution architectures, requirements, and deployment plans.
• Collaborate with engineering, customers, and partners to integrate AI models, hardware accelerators, and security.
• Evaluate models and edge tech, balancing accuracy, latency, power, cost, and reliability.
• Move solutions from proofs of concept to repeatable, deployable offerings delivering customer value.
• Lead cross-functional alignment on KPIs and product goals.

Skills

Edge AI Architecture

AI model optimization

Agentic AI systems

DevOps & production deployment

Edge hardware integration

Education

Bachelor's degree in Engineering/CS

Tools

Python

C/C++

AI frameworks

APIs

Containers/CI-CD

Job description

Manpower San Diego is seeking a Solutions Product Manager for Edge and Agentic AI to define, develop, and bring to market end-to-end AI solutions across edge devices, compute platforms, software, and cloud services.

You will translate customer requirements into solution architectures, reference implementations, and deployment plans, and collaborate with engineering teams, customers, and partners to integrate AI models, hardware acceleration, security, and lifecycle-management tools for scalable