Senior Software Engineer, Agent Infrastructure
Work on building the next generation of agentic AI infrastructure including secure code execution environments, agent state management, model routing and orchestration, identity and authentication, and resource management for long-running agent workflows. Turn emerging ML research ideas into production-ready infrastructure by building core platform capabilities for execution, storage, and state management; prototype and evaluate new technologies; and partner with research teams to align infrastructure with future agent system needs.
Forward Deployed Engineer, Agentic Platform (Public Sector)
Build and ship features for North, Cohere's AI workspace platform; develop autonomous agents that interact with sensitive enterprise data; experiment rapidly and with high quality to engage customers and deliver solutions that exceed expectations; work across the entire product lifecycle from conceptualization to production; lead end-to-end deployment of North in private cloud and on-premises environments, including planning, configuration, testing, and rollout.
Mechanical Engineer & Python Expert - Freelance AI Trainer
Contributors may design graduate- and industry-level mechanical engineering problems grounded in real practice, evaluate AI-generated solutions for correctness, assumptions, and engineering logic, validate analytical or numerical results using Python (NumPy, SciPy, Pandas), improve AI reasoning to align with first principles and accepted engineering standards, and apply structured scoring criteria to assess multi-step problem solving.
Electrical Engineer & Python Expert - Freelance AI Trainer
Contributors may design rigorous electrical engineering problems reflecting professional practice; evaluate AI solutions for correctness, assumptions, and constraints; validate calculations or simulations using Python (NumPy, Pandas, SciPy); improve AI reasoning to align with industry-standard logic; and apply structured scoring criteria to multi-step problems.
Safety Research Internship (Spring/Summer 2026)
As a Cohere Research Intern, you will conduct cutting-edge machine learning research, training and evaluating production large language models. You will focus on research projects aimed at making models better understood, safer, more reliable, more inclusive, and more beneficial for the world. You will disseminate your research results through the production of publications, datasets, and code. Additionally, you will contribute to research initiatives that have practical applications in Cohere's product development. The internship involves collaborating with the Modelling Safety team on implementing novel research ideas related to fairness, safety (including for multiple languages, dialects, and cultural contexts), robustness, generalisation, interpretability, safety for agents with complex read/write actions, and safety for codegen. The project details and topic will be designed collaboratively between the intern and the team, with a goal to publish a paper in a top venue and contribute to open science. The internship may be remote or onsite, with no relocation or housing provided.
Solution Architect
As the Solutions Architect, you will define the technical blueprint for a rapid 12-week transformation cycle stabilizing and optimizing a North American supply chain relaunch for a large enterprise client. You will be accountable for designing the secure cloud environment and shaping the system architecture across data ingestion, storage, model services, optimization logic, and user-facing applications. You will ensure the decision engine is robust enough to move from pilot validation into production use. Working closely with Data Engineers, Business Analysts, Full Stack Engineers, and QA, you will transform a fragmented operational landscape into a secure, auditable, and scalable solution that enhances speed, efficiency, and fiscal gain. Responsibilities include owning end-to-end solution architecture, defining a single-tenant secure cloud environment supporting rapid delivery, collaborating with the Data Engineering Lead on canonical schema, integration patterns, and data transformation rules, architecting the decision engine integrating predictive models, business rules, and optimization solvers, establishing non-functional requirements for production performance and reliability, and providing cross-functional technical leadership to translate business requirements into technical decisions and guide engineering teams.
Deployed Engineer (Toronto)
Co-architect and co-build production AI agents with customer engineering teams. Own the technical win in pre-sales by designing proofs of concept (POCs), answering deep technical questions, and guiding evaluations. Help customers deploy and operate agent-based applications such as conversational agents, research agents, and multi-step workflows. Advise customers post-sale on architecture, best practices, and roadmap-level decisions. Run technical demos, trainings, and workshops for developer audiences. Surface field feedback and contribute reusable patterns, cookbooks, and example code that scale across customers. Occasionally contribute code upstream when it meaningfully improves customer outcomes.
Software Engineering Manager, Autonomous
As the Engineering Manager on the Autonomous team, you will lead and scale a high-caliber team of engineers dedicated to AI agent development and backend systems. You will oversee the technical roadmap for the team, translating architectural complexity into clear product strategies. Your role involves mentoring a diverse group of engineers, supporting their professional growth, and partnering closely with Product and Design to ensure the tools remain intuitive while supporting deep technical capabilities. You will champion a culture of shipping rapidly with a high bar for technical stability and user experience. Additionally, you will clear technical and operational roadblocks to ensure the team operates with high agency and clarity.
Senior Product Designer, Mobile
Own the observability and lifecycle management of AI features across the organization. Build tools and infrastructure to enable teams to develop, monitor, and optimize LLM-powered features. Design and implement closed-loop evaluation pipelines that automatically validate prompt changes. Develop comprehensive metrics and dashboards to track LLM usage, including cost per feature, token patterns, and latency. Create systems that tie user feedback to specific prompts and LLM calls. Establish best practices and processes for the full lifecycle of prompts, including development, testing, deployment, and monitoring. Collaborate with engineering teams across the organization to ensure they have the tools and visibility needed to build high-quality AI features.
Software Engineer, Agent
Design and deliver production-grade AI agents that are highly performant, reliable, and intuitive, central to driving revenue and used in production environments across various industries such as finance, healthcare, and commerce. Have complete ownership and autonomy over the Agent Development Life Cycle (ADLC) from initial pilot through deployment and continuous iteration, including building, tuning, and evolving AI agents while defining ADLC best practices. Partner with large enterprises and startups to understand business challenges and build AI agents that transform operations at scale. Build and evolve Sierra's core platform by surfacing unmet needs, prototyping new tools and features, and collaborating with research, product, and platform teams to shape the future of AI agent development and Sierra's products.
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