AI Solution Architect Engineer, Consumer Personal Systems

Role Overview

We are seeking a highly skilled AI Solution Architect Engineer to design and build advanced AI systems that enhance workflow efficiency across the Consumer Personal Systems & Gaming organization, including Engineering, Marketing, and cross‑functional business teams.

You will also lead the development of an on‑device, offline-capable intelligent support chatbot running on HP PCs to help end users diagnose and resolve issues locally—reducing reliance on customer support channels.

The ideal candidate has strong AI architecture expertise, hands‑on LLM deployment skills (cloud/on‑prem/edge), deep knowledge of on‑device AI acceleration, and the ability to collaborate across engineering and business teams to deliver high‑impact solutions.

Key Responsibilities

• AI Systems for Consumer Personal Systems & Gaming Workflow Optimization
• Design and implement AI automation solutions that improve engineering, marketing, and cross‑team workflows.
• Build scalable RAG (Retrieval‑Augmented Generation) pipelines, internal copilots, and intelligent agents to drive productivity.
• Evaluate and optimize LLMs across cloud, on‑prem, and edge environments based on performance, cost, and hardware constraints.
• Work with stakeholders to discover automation opportunities and deliver measurable efficiency improvements.
• On‑Device, Offline‑Capable Customer Support Chatbot
• Architect and build a local AI chatbot capable of diagnosing PC issues without internet connectivity.
• Implement optimized edge inference pipelines using CPU/GPU/NPU acceleration under strict latency, memory, and power constraints.
• Integrate system logs, telemetry, OS events, and hardware signals for accurate troubleshooting.
• Ensure solution stability, safety, and performance across a wide range of HP PC platforms.
  
  

Requirements

• AI / LLM Engineering
• Experience deploying and optimizing LLMs across cloud, on‑prem, and edge hardware.
• Knowledge of quantization (INT8/FP8/4‑bit), distillation, pruning, and model optimization for constrained devices.
• Understanding of Chain‑of‑Thought (CoT), self‑consistency, and agent-based architectures.
• Retrieval, Data Processing & Evaluation
• Hands-on experience with vector databases (FAISS, Milvus, pgvector, Elastic KNN).
• Ability to design embedding pipelines, chunking strategies, reranking, and retrieval observability (latency, hit-rate, grounding quality).
• Experience developing evaluation and regression testing frameworks for edge devices.
  
  

C. Frameworks & Toolchains in Edge / On‑Device AI Acceleration

• Proficiency with LangChain (LCEL, agents, tools, tracing), LlamaIndex, and Hugging Face Transformers/PEFT.
• Experience using OpenAI / Azure OpenAI SDKs.
• Strong programming skills in Python (FastAPI/asyncio) plus one strongly typed language (C++/Rust/Go/C#).
• Experience with Ryzen AI (NPU) and Radeon GPUs for on‑device or edge LLM inference.
• Familiarity with ONNX Runtime, TensorRT, OpenVINO, DirectML or equivalent inference runtimes.
• Experience profiling and optimizing latency, throughput, and memory usage on constrained hardware.
• Proficiency in CUDA acceleration, including CUDA kernels, CUDA streams, Unified Memory, CUDA Graph execution.
• System Architecture & Infrastructure
• Knowledge of AKS/Kubernetes, hybrid networking, VNet, Private Endpoint, and secure identity models (Managed Identity / RBAC).
• Experience with Docker, CI/CD pipelines (GitHub Actions / Azure DevOps), and versioning of models, indices, and prompts.
• Understanding of enterprise requirements: audit logging, OAuth2/JWT, data governance, telemetry, observability.
  
  

Preferred Qualifications

• Experience building offline or hybrid AI applications on Windows/PC platforms.
• Background in PC system architecture, OS‑level diagnostics, or telemetry pipelines.
• Experience developing customer-facing AI assistants or troubleshooting tools.
• Understanding of Responsible AI, privacy-preserving inference, and secure data handling.
  
  

Soft Skills

• Ability to explain complex AI concepts clearly to both technical and non‑technical teams.
• Strong cross-team collaboration and communication skills.
• Ownership mindset, strong problem‑solving ability, and passion for innovation
  
  

Impact & Scope

• Impacts large functions and leads large, cross-division functional teams or projects.
  
  

Complexity

• Provides highly innovative solutions to complex problems within established policy.
  
  

Disclaimer

• This job description describes the general nature and level of work performed in this role. It is not intended to be an exhaustive list of all duties, skills, responsibilities, knowledge, etc. These may be subject to change and additional functions may be assigned as needed by management.