AI Architect
First seen by Alion on Sep 21, 2026.
Preference : Immediate Joiners
Core Responsibilities :
- Architectural Design : Build scalable, cost-aware systems handling data pipelines, GPU utilization, and model deployment across hybrid or cloud environments.
- Technology & Model Selection : Choose between RAG (Retrieval-Augmented Generation) or fine-tuning, and select the best tools (e.g., LangGraph, TensorFlow, PyTorch) for specific use cases.
- System Integration : Guarantee AI solutions integrate seamlessly with existing IT infrastructure and maintain security standards.
- Governance & Lifecycle Management : Implement MLOps (ModelOps), monitor for latency and hallucinations, and establish automated guardrails.
- Stakeholder Management : Collaborate with executives, data scientists, and engineers to align technology roadmaps with business ROI.
Key Skills & Requirements :
- Technical Proficiency : Deep understanding of Large Language Models (LLMs), neural networks, and orchestration frameworks.
- Data Management : Expertise in vector databases, data readiness, and processing large datasets.
- Cloud & Infrastructure : Familiarity with major cloud providers (AWS, Azure, GCP) and containerization/orchestration tools (Docker, Kubernetes).
- Leadership & Strategy : Exceptional communication and analytical skills to bridge the gap between technical teams and business stakeholders.
Skills
Artificial Intelligence, LLM, Neural Networks, GPU, Data Pipeline, MLOps