AI Solution Architect II

Job description

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 **#body.unify div.unify-button-container .unify-apply-now:** focus, #body.unify div.unify-button-container .unify-apply-#body.unify div.unify-button-container .unify-apply-now: focus, #body.unify div.unify-button-container .unify-apply-