Senior Software Engineer, Agent Infrastructure

Навыки

• Распределённые системы
• Kubernetes
• LLM
• Machine Learning
• Маршрутизация и NAT
• WebAssembly

О компании и продукте

• We’re building the next generation of agentic AI infrastructure at Cohere. This team sits at the intersection of ML systems, distributed infrastructure, and developer experience, creating the platform that powers autonomous AI agents at scale.
• You’ll work on hard, forward-looking problems with few established patterns, including secure code execution, agent state management, model routing, identity and authentication, and resource management for long-running agent workflows.
• This role is a strong fit for someone who combines systems depth with ML intuition. You should be comfortable building reliable infrastructure, thinking through distributed systems tradeoffs, and understanding how emerging agentic capabilities shape platform design.
• Cohere is the leading security-first enterprise AI company. We build cutting-edge foundation AI models and end-to-end products that are designed to solve real-world business problems.

Задачи

• Secure execution environments for agent-generated code
• Identity, authentication, and trust boundaries for agents
• Model routing and orchestration across different model types and environments
• Rate limiting, quotas, and resource management for agent workflows
• State management, memory, and filesystem abstractions for agents
• Turn emerging ML research ideas into production-ready infrastructure
• Build core platform capabilities for execution, storage, and state management
• Prototype and evaluate new technologies, then help decide what should move into production
• Partner with research teams to shape infrastructure based on what future agent systems will need
• YOU MAY BE A GOOD FIT IF YOU HAVE
• Experience building production ML infrastructure with strong systems fundamentals
• Hands-on work with agentic systems, multi-agent workflows, or agent development frameworks
• Familiarity with model routing and LLM provider frameworks across different model types and environments
• Experience with scalable, fault-tolerant distributed systems and Kubernetes
• A track record of moving quickly on prototypes and making good decisions about productionization
• Experience across on-prem, private cloud, and public cloud environments
• Familiarity with storage systems, embedded databases, or filesystem abstractions
• Experience with code execution sandboxes such as gVisor, Firecracker, Kata, or WASM runtimes
• Interest in emerging ML infrastructure, edge inference, or browser-native models
• Open-source contributions to LLM or agent infrastructure projects
• Experience with identity, workload auth, or capability-based security systems
• Compensation

Условия

• For candidates based in California, New York and Washington States, the compensation range is: $215,000 – $325,000
• For candidates based elsewhere in the US, the compensation range is: $180,000 – $275,000
• For candidates based in Canada, the compensation range is: $260,000 – $385,000

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