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Build and maintain an autonomous AI agent platform for hardware validation, designing LLM agent frameworks, RAG pipelines, and developer tooling to automate testing and knowledge management without human intervention.
Lead AI Engineer designs and builds cloud-based AI platforms for accounting, tax, and audit workflows, integrating LLMs (e.g., OpenAI) into scalable backend systems while leading cross-functional teams.
Builds agentic AI systems for commercial real estate using LangGraph, AWS Bedrock, and retrieval pipelines to power research, document generation, and zoning tools for brokers and investors.
Own end-to-end delivery of AI agent security certifications: scope evaluations, build custom integrations by reading API docs and wiring customer systems into AIUC's evaluation platform, and deliver results directly to enterprise clients.
Design and lead large-scale distributed infrastructure for AI systems, including Kubernetes clusters, data pipelines, and developer tooling, ensuring reliability and scalability.
About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of…
Anthropic seeks an Applied AI Strategist to advise EMEA’s top enterprises on AI transformation, shaping executive narratives, and driving adoption of Claude. Focuses on strategic positioning, content creation, and regulatory alignment for high-stakes accounts.
Senior pre-sales role advising EMEA enterprises on securely deploying Anthropic’s AI models. Day-to-day: lead security architecture reviews, explain GDPR/EU AI Act compliance, and design solutions for regulated industries like finance and insurance.
Research Engineer in Reinforcement Learning (RL) at Anthropic develops agentic AI models for autonomous tasks like coding and software generation, advancing Claude’s capabilities while ensuring safety and scalability. Core work spans RL infrastructure, distributed training, and prototype development for internal AI systems.
Build and optimize the reinforcement-learning training infrastructure that lets researchers iterate quickly on model training runs, using distributed systems and ML frameworks like JAX or PyTorch.
Senior engineer builds and scales Kubernetes control planes for AI compute fleets, extending the scheduler and core services to handle thousands of accelerators across multiple clouds.
Build and maintain AI safety systems that detect misuse, monitor model behavior, and enforce safeguards at scale using Python and multi-layered defenses.
Designs and operates AI-scale compute clusters, automating provisioning, security, and lifecycle management across clouds and datacenters to support model training and production services.
Build and maintain the distributed systems that keep Anthropic’s AI models reliable, designing observability, SLAs, and incident response for large-scale model serving across regions and cloud providers.
The Staff Software Engineer will design and maintain high-performance distributed systems to serve Claude models at scale, focusing on request routing, fleet orchestration, and infrastructure optimization. The role involves working across cloud platforms and AI accelerators to ensure reliable, efficient model inference for millions of users.
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