Senior Product Manager - Edge & Agentic AI

Spectraforce Technologies; San Diego (CA); On-site; USD 140,000 - 190,000; Full time

Job summary

Spectraforce Technologies seeks a Senior Product Manager for Edge & Agentic AI to define, develop, and bring to market end-to-end AI solutions spanning edge devices, compute platforms, software, and cloud services.

The role requires hands-on AI/ML knowledge, edge computing, hardware/software integration, and deployment strategy experience, with collaboration across engineering teams, customers, and partners.

Qualifications

• Bachelor's degree in Engineering, Information Systems, Computer Science, or a related technical field.
• 4+ years of Product Management or related work experience.
• Advanced degrees in a relevant field may substitute for up to two years of required experience: Master’s = 1 year, Doctorate = 2 years.

Responsibilities

• Define and develop end-to-end AI solutions spanning edge devices, compute platforms, software, and cloud services.
• Translate customer requirements into solution architectures, technical requirements, reference implementations, deployment plans.
• Work closely with engineering teams, customers, and technology partners.
• Integrate AI models, agentic AI capabilities, hardware acceleration, security, connectivity, and lifecycle‑management tools.
• Evaluate emerging AI models and edge technologies.
• Drive deployments from proofs of concept to repeatable, deployable offerings.

Skills

Edge AI Architecture

AI Models & Inference

Agentic AI

Solution Deployment

Edge Platform

Education

Bachelor's degree in Engineering/CS

4+ years Product Management

Job description

Role: Senior Product Manager - Edge & Agentic AI

Location: San Diego, CA
Duration: 3 months

Job Summary

Client is seeking a Senior Product Manager - Edge & Agentic AI to define, develop, and bring to market end-to-end AI solutions that operate across edge devices, compute platforms, software, and cloud services. This is a highly technical Product Management role requiring hands-on understanding of AI/ML, edge computing, agentic AI, hardware/software integration, and production deployment. The ideal candidate will be able to translate customer requirements and use cases into solution architectures, technical requirements, reference implementations, and deployment strategies, while working closely with engineering teams, customers, and technology partners.

Top 5 Required Skills

• 1. End-to-End Edge AI Solution Architecture
  • Experience designing end-to-end solutions across:
    • Edge devices
    • Compute platforms
    • Operating systems
    • AI runtimes
    • Applications
    • Cloud services
    • Connectivity
    • Security
    • Device management
  • Ability to understand how these components work together in a production environment.
• 2. AI Models & Inference Optimization
  • Strong understanding of:
    • Foundation models
    • LLMs
    • Vision models
    • Multimodal models
    • Model selection
    • Fine-tuning
    • Quantization
    • Model compression
    • Hardware acceleration
  • Ability to evaluate trade‑offs involving:
    • Accuracy
    • Latency
    • Power
    • Cost
• 3. Agentic AI Systems
  • Hands‑on knowledge of:
    • AI agents
    • Tool use
    • Agent orchestration
    • Retrieval‑Augmented Generation (RAG)
    • Context and memory management
    • Workflow automation
    • Guardrails
    • AI evaluation
    • Observability
    • Human‑in‑the‑loop systems
• 4. Solution Development & Production Deployment
  • Experience building prototypes and production‑grade AI solutions using:
    • Python or C/C++
    • AI/ML frameworks
    • APIs
    • Containers
    • CI/CD
    • Cloud‑edge integration
    • Telemetry
    • Testing
    • Lifecycle management
• 5. Edge Platform & Hardware/Software Integration
  • Experience working with:
    • CPUs
    • GPUs
    • NPUs
    • AI accelerators
    • SDKs
    • Drivers
    • AI frameworks
    • Sensors
    • Applications
  • Ability to profile and optimize:
    • Performance
    • Power
    • Thermal constraints
    • Reliability
    • Scalability

Education & Experience

• Bachelor's degree in Engineering, Information Systems, Computer Science, or a related technical field.
• 4+ years of Product Management or related work experience.
• Advanced degrees in a relevant field may substitute for up to two years of required experience:
  • Master's degree = 1 year
  • Doctorate = 2 years

Principal Duties & Responsibilities

• Define and develop end-to-end AI solutions spanning edge devices, compute platforms, software, and cloud services.
• Translate customer requirements and priority use cases into:
  • Solution architectures
  • Technical requirements
  • Reference implementations
  • Deployment plans
• Work closely with engineering teams, customers, and technology partners.
• Integrate:
  • AI models
  • Agentic AI capabilities
  • Hardware acceleration
  • Applications
  • Security
  • Connectivity
  • Lifecycle‑management tools
• Evaluate emerging AI models and edge technologies.
• Validate performance and deployment trade‑offs involving accuracy, latency, power, cost, reliability, and scalability.
• Drive solutions beyond demonstrations and proofs of concept into repeatable, deployable offerings.
• Ensure solutions deliver measurable customer value.
• Conduct complex marketability analyses based on market, customer, technology, and ecosystem requirements.
• Develop business cases for new products and product features, considering time‑to‑market, cost, and market share.
• Prepare and deliver complex technical presentations to customers for new and existing products.
• Define solution requirements for complex products and services with minimal supervision.
• Complete product development and definition activities for assigned products, including cost and impact analysis.
• Maintain expertise on competitors, technology advancements, and the broader product ecosystem.
• Lead product innovation and design efforts within an established product area.
• Identify market and technology trends and articulate product differentiation to customers.
• Communicate product plans across internal and cross‑functional teams.
• Ensure agreed‑upon KPIs and product specifications are achieved upon engineering delivery.
• Collaborate with stakeholders and program sponsors to establish product goals around:
  • Performance
  • Cost
  • Timeline
  • Customer schedules
• Facilitate cross‑functional decision‑making and assess product feasibility.