Principal Engineer, Agentic AI Solutions Lead – Industrial & Embedded IoT, Edge AI ‑Prem Appliance

Principal Agentic Ai Solutions Architect

Qualcomm is a global leader in connected intelligent edge, focusing on AI, edge computing and connectivity. Our fast-growing Industrial and Embedded IoT (IE-IoT) BU leads the transformation of industries through intelligent edge solutions that combine connectivity, compute, and AI. We expand our global talent in applied edge AI to support our customers' digital transformation across many verticals and industries.

AI on-prem Appliance is a new product line under IE-IoT BU. This advanced AI solution is designed for computer vision, generative AI inference and Agentic AI workloads on dedicated on-premises hardware—allowing sensitive customer data, fine-tuned models, and inference loads to remain on premises. It combines the accessibility and performance of a datacenter inference server with power efficiency, form factor, privacy, personalization, and control of an on-premises AI solution.

Qualcomm AI Inference Suite provides ready-to-use AI applications and AI agents, tools, and libraries for operationalizing AI.

Qualcomm is building end-to-end Edge AI solutions for Generative AI (LLM, VLM, VLA), Agentic AI, Voice AI, workloads that are commercially deployed on AI on-prem Appliance. Applications and use cases span various connected devices in on-device, on-prem, and hybrid cloud scenarios. As a Principal Agentic AI Solutions Architect, you will define, develop, document and own scalable and customizable blueprints for different vertical solutions, lead hands-on prototyping, and collaborate closely with customers, partners, product management, customer engineering and other internal teams to tailor deployments for enterprise customers across industries.

We are seeking an experienced, hands-on expert with strong SW skills, solid knowledge of AI hardware, passionate about developing innovative genAI and hybridAI solutions with transformational impact to the industries.

Key Responsibilities:

• Own AI solution blueprints:
  Design, develop, document, and maintain reference designs and delivery playbooks that accelerate repeatable Agentic AI/GenAI/Hybrid-AI deployments on AI on-prem Appliance across priority verticals Lead the design of GenAI blueprints using LLMs, RAG, and agentic workflows to solve enterprise challenges across domains like knowledge management, customer support, and analytics.
• Agentic AI:
  Architect and implement agentic workflows (multi-agent planning, tool use/function calling, memory, safety) using Qualcomm platforms and industry frameworks; define KPIs and evaluation loops. Architect intelligent multi-agent systems with long-horizon reasoning, tool use, and orchestration frameworks (e.g. Lang Chain, Llama Index) to automate complex workflows.
• Vertical customization:
  Partner with Product Management, Account Managers, Regional teams, Engineering and field teams to adapt blueprints to customer-specific requirements/KPIs, data, infrastructure, privacy/security, and compliance constraints; drive solution acceptance and production hand-off.
• Be hands-on:
  Proficient in SW skills;
  Design and develop reference designs, Build POCs and pilot systems; instrument, profile, and optimize models and pipelines end-to-end (latency, throughput, accuracy, cost, power/thermals, footprint). Deliver hands-on prototypes, demos, and reference architectures (e.g. chatbots, summarizers, multimodal assistants) that scale to production and showcase Qualcomm's GenAI stack.
• Multi-model AI expertise:
  Apply and integrate LLMs, VLMs, VLAs, CV/CNN, and NLP stacks; select/quantize/prune/distill models; tune adapters; and integrate guardrails, retrieval, and evaluation frameworks. Build and optimize RAG pipelines with vector databases and semantic search to enable fast, context-rich LLM responses; fine-tune and deploy models on Cloud AI 100 Ultra and other accelerators.
• Solutions focus:
  Deliver production-grade patterns for video analytics, enterprise GenAI (RAG, document AI, code & task copilots), and multimodal agents that interact with enterprise systems and tools.
• Hybrid AI architecture:
  Partition workloads across on-device AI for a variety of edge devices, on-prem/edge boxes, and…