Job description

WHO ARE WE? 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. We’re training and deploying frontier models for enterprises who are building AI systems. We believe that our work is instrumental to the widespread adoption of AI and we are looking for folks that want to be part of that. We obsess over what we build. Each one of us is responsible for contributing to increasing the capabilities of our models and the value they drive for our customers. Cohere is a team of researchers, engineers, designers, and more, who are all passionate about their craft. We are a global technology company headquartered in Toronto with key offices in London, New York City, San Francisco, Montreal, Paris, Berlin and Seoul. Join us! ABOUT THE ROLE. 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. WHAT YOU’LL WORK ON. - 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. IN THIS ROLE YOU WILL: - 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. BONUS - 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. FULL-TIME EMPLOYEES AT COHERE ENJOY THESE PERKS: - A weekly lunch stipend of $75/£75 or equivalent in your local currency for lunch. - Full health and dental benefits, including a 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: Arts & culture, fitness/wellness, quality time, and a workspace improvement credit. Education & learning stipend for conferences, courses, and coaching. - 6 weeks of paid vacation (30 working days!) - Budget for traveling to other offices if you are remote, plus an annual company offsite. HOW AND WHERE WE WORK: - Cohere is remote-friendly, but we also have offices in Toronto, London, New York City, San Francisco, Montreal, Paris, Berlin and Seoul with more opening soon. - For those in the office: a daily lunch program, plenty of snacks, and regular community and social events. - For those not near an office: a co-working benefit so you can work alongside others in your city. - Everyone receives a $500 home office stipend to set up your workspace properly. If any of the above doesn’t line up exactly with your experience, we still encourage you to apply. We strive to create an inclusive work environment for all; we welcome applicants from all backgrounds and are committed to providing equal opportunities. Should you require any accommodations during the recruitment process, please submit an Accommodations Request Form docs.google.com, and we will work together to meet your needs. We may use AI-enabled tools to screen and assess applicants against the criteria for this position. This helps our recruiters identify potentially qualified candidates, but it doesn't limit the applications our recruiters may review or consider. Beware of Scams: Cohere will never ask for payment or third-party services (e.g., CV writing) as part of our hiring process. All legitimate roles are listed on the Cohere careers page and LinkedIn only, with all communications from Cohere employees coming from an @cohere.com or @cw.cohere email alias. If jobs are viewed on other sites then please verify these through our official careers cohere.com page.

Requirements

Must-haves

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.
We are a global technology company headquartered in Toronto with key offices in London, New York City, San Francisco, Montreal, Paris, Berlin and Seoul. Join us!
ABOUT THE ROLE.
WHAT YOU’LL WORK ON.
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

Nice-to-haves

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.

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

aimlllmkubernetes

Platform: ashby
Effort: quick

Benefits

Benefits detected in the listing.

Dental

401k

Parental Leave

Wellness