Senior Software Engineer, Agent Infrastructure

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.

Responsibilities

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

Requirements

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

Nice to have

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

Benefits

Weekly lunch stipend of $75/£75 or equivalent in local currency; Full health and dental benefits, including separate budget for mental health; RRSP matching, 401K, Pension Scheme; 100% Parental Leave top-up for up to 6 months for either parent; Annual enrichment benefits including arts & culture, fitness/wellness, quality time, workspace improvement credit, and education & learning stipend; 6 weeks of paid vacation (30 working days); Budget for traveling to other offices if remote, plus annual company offsite; Daily lunch program, snacks, and regular community and social events for office-based employees; Co-working benefit for those not near an office; $500 home office stipend