AI Architect
Indexed description
- Define enterprise level AI architecture and design patterns for ML, Generative AI, and Agent based systems
- Establish reference architectures for common AI use cases (RAG, copilots, predictive models, automation, decision intelligence)
- Guide AI Engineers and Data Scientists in designing scalable, cost efficient, and production ready AI solutions
- Partner with business leaders to translate strategic objectives into AI solution roadmaps
- Ensure alignment with security, privacy, compliance, and responsible AI policies
- Evaluate AI platforms, frameworks, and vendors (cloud AI services, LLM providers, vector databases, orchestration tools)
- Define MLOps / LLMOps standards for model lifecycle, monitoring, observability, and retraining
- Support AI adoption enablement by contributing to internal best practices, architecture reviews, and technical forums
- Review and approve AI designs before production rollout
Required Skills & Experience
- Strong experience (8+ years preferred) in software and/or data architecture, with hands on AI exposure
- Deep understanding of:
- Machine Learning and Deep Learning architecture
- Generative AI (LLMs, embeddings, RAG, fine tuning)
- Agentic and workflow based AI systems
- Expertise in cloud platforms (Azure, AWS, or GCP) and AI services
- Experience designing microservices, APIs, event driven architectures
- Strong knowledge of security, IAM, encryption, and data governance in AI systems
- Ability to communicate architecture decisions to technical and non technical stakeholders
Qualifications: BACHELOR OF COMPUTER SCIENCE
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