6 часов назад
AI Architect (AI)
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
Текст:
TL;DR
AI Architect (AI): Defining architecture strategies and reusable patterns for production AI platforms and applications with an accent on agentic systems, multi-agent workflows, RAG pipelines, and cloud infrastructure. Focus on designing scalable and secure systems, governing architecture standards, making build-versus-buy decisions, and enabling cross-functional engineering teams.
Location: UK-Hayes-Hyde Park Hayes
Company
Technology provides end-to-end hybrid cloud and AI solutions, including the design, construction, operation, modernization, and optimization of customer cloud environments.
What you will do
- Define and own architecture strategies for AI platforms and applications across .
- Design scalable, reusable patterns for agentic systems, multi-agent workflows, RAG pipelines, and orchestration frameworks.
- Define non-functional requirements covering scalability, latency, cost efficiency, and security.
- Create architecture standards, lead design reviews, and govern consistency across engineering teams.
- Lead build-versus-buy-versus-partner decisions for AI tooling, frameworks, and infrastructure.
- Shape the AI engineering roadmap, mentor engineers, and promote responsible AI and AI-native development practices.
Requirements
- Experience designing complex distributed systems and governing architecture at an organizational level.
- Production experience with agentic systems, RAG pipelines, and LLM-integrated applications.
- Expert-level Python, including asynchronous programming, testing, packaging, and production engineering.
- Deep AWS cloud architecture expertise across compute, networking, storage, and managed AI services.
- Production experience with LangChain, LangGraph, and AWS Bedrock.
- Experience designing and governing Kubernetes workloads, including Helm and resource management, plus end-to-end frontend and backend system design.
Nice to have
- Experience with internal developer platforms, AI enablement tooling, prompt engineering, evaluation frameworks, or LLM observability.
- Knowledge of MLOps, including model versioning, monitoring, and drift detection.
- Platform engineering experience with GitOps, service mesh, and infrastructure as code using Terraform or CDK.
- Experience with multi-cloud or hybrid cloud environments, AI security, governance, responsible AI, or open-source AI tooling.
Culture & Benefits
- Work within the internal AIR team, building reusable AI infrastructure, agentic workflows, and full-stack applications.
- Collaborate with product, data, platform, and engineering teams across the organization.
- Contribute to an environment that values pragmatic architectural trade-offs, technical growth, and responsible AI.
- Full-time employment with Technology.
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