Software Engineer II - Cloud-Native Agent Harness (Mecatl)

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Software Engineer II – Cloud-Native Agent Harness (Mecatl) based in Canada. Join an innovative engineering team building the next generation of secure, cloud-native infrastructure for enterprise AI agents. In this role, you will contribute to the development of an open-source agent harness designed to run autonomous AI agents reliably and securely at scale. You will work across backend systems, Kubernetes-native infrastructure, developer tools, APIs, and security frameworks. The position offers significant technical ownership, allowing you to drive features and improvements from design through implementation and release. You will also work in an AI-first engineering environment, using AI agents in your development workflow and helping shape best practices for their adoption. This is an opportunity to influence emerging AI infrastructure while collaborating with experienced engineers in an open-source, fast-moving environment. Accountabilities: - Design, develop, and deliver features across the cloud-native agent harness, including agent execution loops, tool integrations, permission systems, session management, and Kubernetes-based runtime components. - Contribute to client-facing interfaces and developer tools, including gRPC, APIs, TypeScript SDKs, and command-line applications. - Improve platform reliability, security, performance, and observability to ensure production-ready agent infrastructure. - Write clean, maintainable, testable code with appropriate error handling and edge-case coverage. - Produce technical documentation and design proposals, participate in code reviews, and provide constructive feedback on contributions, including AI-generated code. - Take ownership of assigned projects, translating product requirements into technical solutions and delivering improvements independently.

- Integrate AI coding agents into daily development activities, critically evaluating their output and ensuring code quality, security, and reliability. - Experiment with AI-assisted engineering workflows, identify opportunities for improvement, and share practical findings with the wider team. - Apply sound security practices when working with AI systems, particularly around permissions, secrets management, untrusted inputs, and agent autonomy. - Collaborate with engineering and product stakeholders while contributing to the open-source community and supporting developers using the platform. Requirements: - Professional proficiency in Go, with experience writing clean, maintainable, and testable code. - Demonstrated ability to independently develop, test, and deliver features within backend, platform, or infrastructure-focused software projects. - Working knowledge of distributed systems and cloud-native technologies, particularly Kubernetes, containers, and service APIs such as gRPC or - Familiarity with concurrency, streaming architectures, durable state management, or distributed application development is an advantage. - Hands-on experience using AI coding agents in software development, with the ability to explain their practical benefits, limitations, and associated risks, including prompt injection and excessive agent permissions. - Strong interest in AI agent infrastructure, including agent execution frameworks, tool integrations, Model Context Protocol (MCP), model providers, and evaluation systems. - Previous experience contributing to open-source projects or developing AI platforms is an advantage. - A product-oriented engineering mindset, with curiosity about user needs, the ability to challenge assumptions, and a focus on delivering practical solutions. - An AI-first approach to software development, using AI tools thoughtfully to accelerate engineering processes and improve the quality of delivered products.