Gautam Buddha Nagar, Uttar Pradesh

Job Summary

Role Summary

Level : Principal Engineer

Primary Focus : AI workload optimization on Intel AI PCs

Customer advisory + solutioning

Key Responsibilities

Technical Leadership

Intel Core Ultra (CPU + GPU + NPU)

Hybrid AI workloads (cloud + edge + endpoint)

Design and implement solutions using : Intel OpenVINO Toolkit

Intel oneAPI (DPC++, MKL, etc.)

Enable AI inferencing on edge / endpoint devices (AI PCs)

Solution Architecture & Innovation

Define reference architectures for : AI PC-based Digital Workplace

Edge inferencing use cases

Build reusable optimization frameworks, accelerators, and toolkits.

Drive performance benchmarking and tuning for enterprise workloads.

Managed Services Development

Design and operationalize : Continuous performance tuning services

Create : Service catalog

SLAs / KPIs

Automation frameworks

Ecosystem Collaboration

Work closely with : Intel engineering & solution teams

ISVs and OEMs

Align with Intel programs : AI PC acceleration

vPro / EMA integrations

Customer Engagement

Function as SME / Advisor in : Pre-sales discussions

Solution workshops

PoCs / pilots

Translate customer workloads into : Optimized AI-enabled solutions

Revenue & Practice Building

Build a self-sustaining practice around : AI PC optimization services

Support : Deal shaping

Value articulation (ROI, performance gains)

Enable internal teams through : Training

Playbooks

GTM assets

Key Responsibilities

Key Deliverables expected

Establish baseline capabilities.

Identify top 3-5 use cases for AI PC optimization.

Build initial PoCs.

Develop : Reference architectures

Optimization frameworks

Initiate pilot engagements with customers

Launch : Managed services offering

Enable : Sales + delivery teams

Contribute to :



Revenue pipeline and wins

Success Metrics (KPIs)

Technical

Number of workloads optimized for AI PC

Business

Revenue generated from optimization services

Number of customer engagements / PoCs converted.

Practice Growth

Reusable assets created

Teams enabled / trained.

Skill Requirements

Required Technical Skills

Core Expertise

Intel OpenVINO Toolkit (Advanced)

Intel oneAPI (DPC++, oneMKL, oneDNN, etc.)

AI model optimization : Quantization

Pruning

Model conversion

AI / ML Stack

Frameworks : TensorFlow

PyTorch

ONNX

Experience with : Model deployment pipelines.

Edge inferencing

Hardware & Systems Knowledge

Deep understanding of : Intel Core Ultra architecture (CPU + GPU + NPU)

Heterogeneous computing

Performance profiling tools : VTune

Intel Advisor

Software Engineering

Languages : Python (mandatory)

C++ (preferred)

API integration and system-level optimization

Enterprise Workplace Context

Understanding of : Digital Workplace / EUC environments

Endpoint management (e.g., vPro, EMA)

Experience optimizing : Collaboration tools

Other Requirements

Preferred Experience

Prior experience working with : Intel ecosystem or partner programs

OEMs (HP, Dell, Lenovo)

Exposure to : Edge AI / IoT solutions

Industry verticals (E&U;, Manufacturing, BFSI)

Experience in : Managed services or AMS models

Business & Consulting Skills

Solid customer-facing communication

Ability to : Articulate technical value in business terms.

Build ROI-driven narratives.

Experience in : Pre-sales / solution consulting

Stakeholder management

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📌 Technical Lead (Gautam Buddh Nagar)
🏢 HCLTech
📍 Gautam Buddh Nagar