Why This Job is Featured on The SaaS Jobs
Work on agent infrastructure sits at a pivotal layer of the current SaaS stack, where AI capabilities become dependable, repeatable product features. This role stands out because it targets the operational backbone of agentic systems, including secure execution, state, routing, and identity, which are the areas that determine whether AI agents can be offered as a reliable service to developers and enterprises. The remit signals a platform-oriented SaaS environment where internal infrastructure directly shapes what customers can build.
For a SaaS career, this kind of infrastructure scope builds durable leverage. It develops judgment around distributed systems tradeoffs, multi-tenant resource controls, and production security boundaries, all central to running software as a service at scale. It also provides experience translating emerging ML research into stable platform primitives, a recurring challenge for teams productizing AI while maintaining uptime, cost discipline, and predictable behavior.
The role fits engineers who prefer foundational work over feature delivery and who enjoy ambiguous problem spaces with few established patterns. It will suit someone comfortable collaborating across research and product engineering, and motivated by building systems that other developers depend on. Remote eligibility also aligns with candidates who work effectively with written context and asynchronous coordination.
The section above is editorial commentary from The SaaS Jobs, provided to help SaaS professionals understand the role in a broader industry context.
Job Description
Who are we?
Our mission is to scale intelligence to serve humanity. We’re training and deploying frontier models for developers and enterprises who are building AI systems to power magical experiences like content generation, semantic search, RAG, and agents. We believe that our work is instrumental to the widespread adoption of AI.
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. We like to work hard and move fast to do what’s best for our customers.
Cohere is a team of researchers, engineers, designers, and more, who are passionate about their craft. Each person is one of the best in the world at what they do. We believe that a diverse range of perspectives is a requirement for building great products.
Join us on our mission and shape the future!
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.
If some of the above doesn’t line up perfectly with your experience, we still encourage you to apply!
We value and celebrate diversity and 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, and we will work together to meet your needs.
Full-Time Employees at Cohere enjoy these Perks:
🤝 An open and inclusive culture and work environment
🧑💻 Work closely with a team on the cutting edge of AI research
🍽 Weekly lunch stipend, in-office lunches & snacks
🦷 Full health and dental benefits, including a separate budget to take care of your mental health
🐣 100% Parental Leave top-up for up to 6 months
🎨 Personal enrichment benefits towards arts and culture, fitness and well-being, quality time, and workspace improvement
🏙 Remote-flexible, offices in Toronto, New York, San Francisco, London and Paris, as well as a co-working stipend
✈️ 6 weeks of vacation (30 working days!)
