Software Engineer, Sandbox & Agent Executor

Retool • San Francisco, CA

5d

About The Position

We build products where agents write and run code, and where the environment that code runs in is ours to own. As agents get more capable, users go from prompt to working app in minutes instead of hours, and increasingly they expect agents that don't just generate the app but run the work inside it. We're looking for engineers who have shipped agentic products into production and kept them running reliably, affordably, and at scale, and who want to bring that experience to developer-facing surfaces used every day by real engineering teams.

Requirements

• 6+ years of professional engineering experience, with ownership over complex systems in production
• Production experience with agentic systems, including context engineering, tool use, and evaluation frameworks, at real user scale rather than in pilots or demos
• Hands-on experience with sandboxing technology and running agents inside sandboxed environments
• Experience in Kubernetes or equivalent in practice (EKS, ECS, or similar), owning services end to end
• Strong systems thinking, with the instinct to use AI as an augment to engineering judgment rather than a replacement for it
• Curiosity in why a model produced what it did, and the habit of checking rather than assuming
• Experience mentoring engineers on this kind of work, including when to lean on a model and when not to

Nice To Haves

• Experience building for developer surfaces like CLIs, IDE extensions, or coding harnesses
• Experience shipping into enterprise or air-gapped environments, where you debug systems you can't directly observe

Responsibilities

• Own the behavior of agentic features across multiple product surfaces, including quality, safety, variance, and failure modes, and shape the tool and harness surface agents operate against, including MCP servers, sub-agents, and skills
• Work across the product and infrastructure boundary, shaping agent behavior while understanding what it costs at runtime, and serve as the infrastructure team's technical counterpart on agent workloads
• Design and evolve prompting, context construction, retrieval, routing, and tool-use strategies for long-horizon workflows, and build the evaluation systems that measure them through statistical signals, distributions, and trends rather than pass/fail tests
• Detect, diagnose, and resolve non-deterministic failures such as hallucinations, partial correctness, instruction drift, or context sensitivity, working from transcripts and traces rather than logs alone
• Partner closely with product and infrastructure teams on how agent workloads are provisioned, isolated, and rolled out, including for self-hosted customers, and set the pattern for how we ship agentic products safely

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: No Education Listed