Description

You own the architectural design and implementation of end-to-end AI systems.

Responsibilities

• Design and implement AI architectures covering data pipelines, model development, inference, monitoring, and production integration.
• Lead architectural strategy for agentic AI systems, focusing on planning, memory, reasoning, and autonomous decision-making.
• Define modular, reusable, cloud-native, and hybrid (AWS/GCP) architectural patterns for scalable AI solutions.
• Serve as the technical architecture leader within AI Office and Agile squads, aligning decisions with product roadmaps.
• Establish AI Ops, governance, and innovation practices, including MLOps and responsible AI.

Required Skills

• 7+ years of experience in solution architecture, with hands-on AI/ML system experience.
• Expertise across the AI lifecycle, including agentic and autonomous AI systems.
• Practical experience with MLOps and LLMOps tooling (MLflow, SageMaker, Vertex AI).
• Proficiency with agent orchestration frameworks (LangChain, AutoGPT, CrewAI, multi-agent systems).
• Strong foundation in Agile software development and cross-functional squad collaboration.
• Proficiency with cloud-native and distributed architectures (AWS, Azure, GCP).
• Experience with containerization (Docker/Kubernetes), microservices, and API design.
• Understanding of enterprise architecture, data governance, and responsible AI practices.

Key Skills

Education

Any Gradute