AI Solution Architect II
India
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Job Description
AI Solution Architect II
Noida, Uttar Pradesh

Job Summary

We are looking for an AI Enterprise Architect to lead the architecture, design, and standardization of our Physical AI platform (e.g., VisionX) and its deployment across enterprise environments. This role will define the end-to-end architecture for AI systems that operate in the physical world—combining computer vision, edge AI, IoT/OT integration, cloud services, digital twin, and agentic AI.

You will work across product engineering, platform teams, and vertical account teams to ensure our solutions are scalable, reusable, secure, and production-ready. You’ll be expected to balance innovation with operational rigor, and align architecture decisions with business outcomes and delivery realities.

Key Responsibilities

 Key Responsibilities  1. Enterprise AI & Physical AI Architecture Define end-to-end architecture across: Edge AI (camera-based systems, IoT, GPU devices) Cloud AI platforms Enterprise systems integration Design architectures for: VisionX-like platforms (video analytics, safety AI, inspection) Digital twin / simulation systems (Omniverse, etc.) Establish architecture principles: modularity, reusability, scalability platform-agnostic design (avoid vendor lock-in) edge-cloud hybrid deployment  2. Generative AI & Multimodal Systems Architect solutions using: LLMs (OpenAI, Claude, Gemini, open-source) Multimodal models (text + image + video) Design: Retrieval-Augmented Generation (RAG) enterprise knowledge systems copilots and conversational interfaces Define: prompt engineering strategies grounding mechanisms evaluation frameworks 3. Agentic AI & Autonomous Systems Design agent-based systems: multi-agent orchestration task planning and execution tool/API integration Build frameworks for: autonomous workflows decision-making systems human-in-the-loop control Evaluate and integrate: LangChain, LangGraph, Semantic Kernel, custom frameworks 4. Computer Vision & Edge AI Systems Architect real-time AI systems for: object detection, tracking, activity recognition multi-camera video analytics Define edge AI strategies: on-device vs centralized inference latency and throughput optimization Design systems using: NVIDIA DeepStream, Triton, TensorRT Jetson / GPU-based edge devices 5. AI Platform, MLOps & DevOps Define platform architecture for: model lifecycle (training → deployment → monitoring) CI/CD for AI and edge systems Establish: model versioning and registry drift detection and feedback loops deployment automation (OTA updates for edge)  6. Data, Integration & Knowledge Systems Design unified data architecture: structured + unstructured + streamin

Skill Requirements

🔹 AI / ML Foundations

  • Strong expertise in:
    • ML, deep learning
    • NLP, computer vision
  • Hands-on with:
    • PyTorch / TensorFlow

🔹 Generative AI

  • LLMs, prompt engineering
  • RAG architectures
  • embeddings, vector DBs (FAISS, Pinecone)

🔹 Agentic AI

  • multi-agent systems
  • orchestration frameworks (LangChain, LangGraph, etc.)
  • tool-calling and workflow automation

🔹 Computer Vision & Edge AI

  • video analytics pipelines
  • DeepStream, Triton
  • TensorRT optimization
  • edge devices (Jetson, GPUs)

🔹 Systems & Cloud

  • microservices architecture
  • APIs, event-driven systems
  • Kubernetes, Docker
  • cloud platforms (Azure/AWS/GCP)

🔹 Data & Integration

  • data engineering concepts
  • knowledge graphs (preferred)
  • enterprise system integration

🔹 Architecture & Governance

  • enterprise architecture frameworks
  • security and compliance
  • scalability and reliability design

Preferred Skills

  • Digital twin / simulation (Omniverse)
  • IoT / OT systems (SCADA, PLCs)
  • Experience in manufacturing / industrial domains

Experience building enterprise AI platforms

Other Requirements

Leadership & Behavioral Competencies

  • Strong systems thinking and ability to simplify complexity.
  • Ability to balance innovation with practical delivery constraints.
  • Excellent communication skills—can explain architecture to engineers, business stakeholders, and customers.
  • Strong collaboration and influence across matrix organizations.
  • Ownership mindset with focus on measurable business outcomes
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Information at a Glance

Why HCLTech?

At HCLTech, you'll supercharge your potential. You'll find your career. And you'll find your spark. All at a place that knows that helping its customers stay on top starts by putting its people first.

HCLTech is a global technology company, home to more than 223,000 people across 60 countries, delivering industry-leading capabilities centered around digital, engineering, cloud and AI, powered by a broad portfolio of technology services and products. We work with clients across all major verticals, providing industry solutions for Financial Services, Manufacturing, Life Sciences and Healthcare, Technology and Services, Telecom and Media, Retail and CPG, and Public Services. Consolidated revenues as of 12 months ending June 2026 totaled $14.8 billion.