Stacklok - Software Engineer II - Cloud-Native Agent Harness (Mecatl)
Requirements
• We do not expect every candidate to meet every point below. If this role excites you and you bring most of it, we encourage you to apply. • Proficiency in Go, writing clean, testable code that accounts for edge cases and error handling, plus clear design docs and thoughtful code reviews. • Demonstrated ability to deliver features independently across a backend or platform codebase, from implementation through testing and into a release. • Working knowledge of distributed systems and cloud-native infrastructure, such as Kubernetes, containers, and service APIs (gRPC or HTTP). Experience with durable state, concurrency, or streaming is a plus. • A personal AI-assisted development workflow you can walk through, with a clear sense of where it helps, where it breaks, and its risks, such as prompt injection and excessive agent permissions. • Interest in agent infrastructure, such as agent loops, tool use, MCP, model providers, or evaluation. Prior experience building on or contributing to an AI platform or open source project is a plus. • Ideally, a product engineering mindset: curious about users and their problems, comfortable questioning requirements, and motivated by shipping something people use. • AI-first mindset: builds AI into the development workflow to accelerate delivery, improve the quality of what ships, and rethink how problems get solved. • Communication: excellent written and verbal communication, able to explain complex technical ideas clearly to technical and non-technical audiences. • Startup mentality and intrinsic motivation: self-directed and hands-on, thrives in fast-moving, ambiguous environments, and drives clarity through action. • Compensation: The anticipated base salary range for this position is $157,500 - $192,500. In addition to base salary, this role offers equity and a comprehensive benefits package.
Responsibilities
• Build and deliver features in the open across Mecatl, including the agent loop, tool and permission systems, session and state management, the Kubernetes runtime, and client SDKs. • Fix bugs and harden the harness for production use, improving reliability, security, and observability. • Write testable, readable code that accounts for edge cases and error handling, produce clear design docs for the work you take on, and review pull requests, including AI-assisted changes. • Understand outcomes and partner with the team anchor to break down the work. Escalate decisions to product or staff engineers as needed. • Use AI agents as a core part of your own workflow, and bring a critical eye to what they produce: review it, test it, and own it. • Find where your AI workflow breaks down on Mecatl work, experiment to fix it, and bring structured findings back so the team gets faster and better, not just busier.
Benefits
• $157,500 - $192,500
Apply in one click
Upload My Resume
Drop here or click to browse · Tap to choose · PDF, DOCX, DOC, RTF, TXT