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

Jobgether; Canada; Hybrid; CAD 220,000 - 269,000; Full time

Benefits offered by this job

Equity opportunities

Healthcare coverage

Remote/hybrid

Paid time off

Parental leave

Team offsites

Professional growth

Technical ownership

Open-source projects

AI-first culture

Job summary

Mecatl is seeking a Software Engineer II in Canada to help build and optimize a cloud-native agent harness for autonomous AI agents. You will work across the backend, Kubernetes-based runtime, and developer tools, delivering features from design through release.

The role emphasizes AI-first development, security, observability, and collaboration within an open-source environment. Remote or hybrid arrangements are supported.

Qualifications

• Professional proficiency in Go, with experience writing clean, maintainable, and testable code.
• Independent development, testing, and delivery of features within backend/infrastructure projects.
• Knowledge of distributed systems and cloud-native tech, especially Kubernetes, containers, and service APIs like gRPC or HTTP.
• Confort with concurrency, streaming architectures, durable state management, or distributed app development is a plus.
• Hands-on AI coding agents experience in software development; able to explain benefits, limitations, and risks including prompt injection and permissions.
• Strong interest in AI agent infrastructure (execution frameworks, MCP, model providers, evaluation)
• Open-source contribution or AI platform development experience is a plus.
• Product-minded engineering, curiosity about user needs, and delivering practical solutions.
• AI-first approach to development; use AI tools to accelerate work while ensuring quality.
• Excellent written and verbal communication; able to explain complex tech to diverse audiences.
• Strong problem-solving, analytical abilities; proactive in resolving challenges.
• Self-motivation, adaptability, independence in fast-paced environments.
• Collaborative mindset and willingness for knowledge sharing and improvement.

Responsibilities

• Design, develop, and deliver features across the cloud-native agent harness (execution loops, tool integrations, permissions, session management).
• Contribute to client-facing interfaces and developer tools (gRPC, HTTP/SSE APIs, TypeScript SDKs, CLI).
• Improve platform reliability, security, performance, and observability for production-ready infra.
• Produce clean, testable code with robust error handling.
• Create technical docs and design proposals; participate in code reviews and provide feedback on AI-generated code.
• Own assigned projects from requirements to implementation and release.
• Integrate AI coding agents into daily workflows; assess output for quality and security.
• Experiment with AI-assisted workflows; share findings with the team.
• Apply security best practices for AI systems (permissions, secrets, untrusted inputs).
• Collaborate with stakeholders and support open-source community.

Skills

Go

Distributed systems

Kubernetes

Containers

gRPC

HTTP APIs

AI tooling

Backend development

Code testing

Open-source

Tools

TypeScript SDKs

Job description

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, HTTP/SSE 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 HTTP.
• 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.
• Excellent written and verbal communication skills, with the ability to explain complex technical concepts to both technical and non-technical audiences.
• Strong problem-solving and analytical abilities, combined with a proactive approach to identifying and resolving challenges.
• Self-motivation, adaptability, and the ability to work independently in a fast-paced environment characterized by evolving priorities and technical challenges.
• A collaborative mindset and willingness to contribute to team development, knowledge sharing, and continuous improvement.

Benefits

• Competitive salary: Anticipated annual base salary range of USD $157,500–$192,500.
• Equity opportunities: Additional equity compensation as part of the overall package.
• Comprehensive healthcare: Medical, dental, and vision insurance coverage.
• Remote flexibility: Flexible remote or hybrid working arrangements.
• Paid time off: Flexible paid time off and paid holidays.
• Parental support: Paid parental leave.
• Team collaboration: Company offsites and opportunities to connect and collaborate in person.
• Professional growth: Opportunities to work alongside experienced professionals in open-source technologies, cloud-native infrastructure, cybersecurity, and AI development.
• Technical ownership: Freedom to make meaningful engineering decisions and contribute to foundational AI infrastructure.
• Innovation-driven environment: An AI-first culture that encourages experimentation, continuous learning, and the responsible adoption of emerging technologies.
• Open-source community: Opportunities to contribute to impactful projects and collaborate with developers and communities worldwide.

We appreciate your interest and wish you the best!