Senior Fullstack Engineer, Agent Platform

About the Role

Commure is hiring a Senior Software Engineer to own the platform powering our fleet of OpenClaw agents.

Across Commure, we use autonomous agents to support teams, execute operational workflows, interact with internal systems, and turn organizational knowledge into action. As the number and capabilities of these agents grow, we need a strong technical foundation for deploying, operating, observing, and improving them safely at scale. You’ll own that foundation.

This role sits at the intersection of platform engineering and applied AI. You’ll build the infrastructure that runs our agents, develop the harnesses that govern how they reason and act, and establish the tools engineers need to create and deploy new agents quickly. You’ll also operate the existing agent fleet and ensure it remains secure, reliable, observable, and cost-efficient.

We’re looking for a strong Python engineer with deep Linux fundamentals who can own both the agent software and the environments where it runs. The ideal candidate combines platform-engineering rigor with practical experience building LLM-powered agents and is comfortable moving between Python application code, Bash-based operational work, Linux virtual machines, Kubernetes, and cloud infrastructure.

This is a hands-on role for someone equally comfortable working inside a Linux VM, debugging a Kubernetes workload, writing Python services and automation, designing an agent tool interface, investigating an LLM failure, and improving a deployment pipeline.

What You’ll Do

• Own the infrastructure and runtime environment for Commure’s fleet of OpenClaw agents.

• Build, configure, deploy, and troubleshoot agents running across Linux-based virtual machines.

• Develop Python services, automation, operational tooling, and agent integrations.

• Design, build, and operate agent harnesses that support tool use, memory, context management, permissions, scheduling, retries, and human escalation.

• Create a standardized platform for engineers to develop, test, deploy, and update agents safely.

• Deploy and operate agent workloads across Linux virtual machines, Kubernetes, and cloud infrastructure on Google Cloud or AWS.

• Use Bash and standard Linux tooling to investigate system behavior, automate environment management, and resolve production issues.

• Build reliable systems for agent scheduling, background execution, queues, concurrency management, and long-running tasks.

• Develop integrations that allow agents to interact with internal services, databases, APIs, communication platforms, and operational tools.

• Establish secure approaches to secrets, credentials, identity, permissions, and access control for autonomous agents.

• Build evaluation frameworks that measure agent reliability, task completion, tool accuracy, latency, and cost.

• Implement production observability across agent traces, prompts, tool calls, infrastructure, failures, and resource consumption.

• Create dashboards, alerting, and incident-response processes for agent and platform health.

• Diagnose failures across application code, model behavior, third-party tools, networks, containers, virtual machines, and cloud infrastructure.

• Improve the efficiency and resilience of the platform as agent usage and workload complexity grow.

• Work closely with product engineers and internal teams to convert promising agent prototypes into dependable production systems.

• Establish best practices for developing and operating autonomous agents across Commure.

What You Have

• Professional experience building and operating production software, infrastructure, or internal platforms.

• Strong proficiency in Python, which will be the primary language for agent development, platform tooling, integrations, and automation.

• Excellent familiarity with Linux environments and hands-on experience developing, deploying, and debugging software on virtual machines.

• Strong Bash and command-line skills, including shell scripting, process management, networking diagnostics, filesystem operations, package management, and log investigation.

• Experience managing software across fleets of virtual machines, including configuration, deployment, monitoring, access management, and failure recovery.

• Strong hands-on experience building and operating production systems on Google Cloud Platform or Amazon Web Services, including compute, networking, storage, identity and access management, and observability.

• Experience deploying and managing Linux virtual machines and containerized workloads in cloud environments.

• Hands-on experience with Kubernetes, Docker, and containerized production workloads.

• Experience building infrastructure, deployment systems, internal developer platforms, or distributed application runtimes.

• Experience with CI/CD, infrastructure as code, configuration management, secrets management, and automated deployments.

• Hands-on experience building with large language models, autonomous agents, or agent harnesses.

• An understanding of agent concepts such as tool calling, memory, context management, planning, retries, evaluations, permissions, and human-in-the-loop execution.

• Experience monitoring and debugging distributed systems using logs, metrics, traces, dashboards, and alerts.

• A strong understanding of production reliability, including failure recovery, idempotency, rate limiting, concurrency management, and incident response.

• The ability to balance fast experimentation with the security and reliability required for production systems.

• Strong ownership and communication skills, including comfort working across product, infrastructure, security, and operational teams.

• A builder mindset and excitement about creating infrastructure for a rapidly evolving category of software.

Nice to Have

• You have built, extended, deployed, or operated an OpenClaw agent.

• You have contributed to OpenClaw or another open-source agent framework.

• Experience operating a fleet of autonomous or long-running AI agents.

• Experience building multi-tenant agent platforms or internal developer platforms.

• Experience with agent evaluation, tracing, replay, simulation, or regression testing.

• Experience with browser agents, computer-use agents, or agents that interact with external systems.

• Familiarity with model gateways, inference providers, prompt versioning, token accounting, and LLM cost optimization.

• Experience securing workloads that access sensitive data or high-impact production tools.

• Familiarity with Swift and experience contributing to or supporting native Apple client applications.

• Experience in healthcare, revenue cycle management, or another regulated industry.

What Success Looks Like

Within your first several months, you will:

• Develop a deep understanding of our existing OpenClaw agents, infrastructure, and operational workflows.

• Make the agent fleet easier to deploy, observe, debug, and maintain.

• Establish clear reliability and performance metrics for agents running in production.

• Reduce the time required to take an agent from prototype to production.

• Improve safeguards around credentials, permissions, tool execution, and sensitive data.

• Improve the reliability, repeatability, and security of our Linux VM and Kubernetes-based agent environments.

• Create a platform that allows Commure teams to build increasingly capable agents without reinventing the underlying infrastructure.