Open position · Autonomous Systems Operations
Autonomous systems are powerful — but not perfect. You are the critical bridge between machine intelligence and real-world execution, stepping in precisely when automation reaches its limits.
The role
As AI systems scale into real-world environments, edge cases, ambiguity, and unexpected situations remain inevitable. As a Human-in-the-Loop Operator, you monitor live autonomous systems — robotics, delivery agents, digital workers — and intervene when they reach the boundary of their confidence. You don't just catch failures; you generate the structured feedback that makes future failures less likely. Every override you file, every edge case you resolve, every anomaly you document makes the system smarter. You are not a fallback. You are a core part of the intelligence loop.
What you'll do
Real-time monitoring
Watch AI-driven systems across robotics, autonomous vehicles, and digital agents
Detect when a system is hesitating, stuck, or operating outside its confidence range
Track multiple concurrent agent streams without losing situational awareness
Escalate critical incidents to engineering and operations teams
Intervention & override
Review and validate system decisions in uncertain or high-risk scenarios
Override agent actions when required — decisively and without overcorrecting
Guide systems through unexpected obstacles, environment changes, or ambiguous inputs
Handle escalations from AI-powered customer systems on behalf of end users
Feedback & improvement
Provide structured feedback to engineering teams after every intervention
Tag and categorize real-world scenarios for training data improvement
Identify recurring failure patterns and submit root-cause reports
Help define confidence thresholds and escalation triggers with the systems team
Documentation
Log incidents, anomalies, and system behaviors with precision and context
Maintain accurate override records for compliance and audit purposes
Contribute to runbooks and escalation playbooks for new scenario types
Flag documentation gaps when novel edge cases lack established procedures
Example tasks on a typical shift
Failed delivery assist
Guide an autonomous system through an incomplete drop-off
Obstacle resolution
Pilot a robot through unexpected environment changes
Decision review
Validate flagged AI decisions for accuracy or safety risk
Customer escalation
Take over from an AI agent that has reached its limit
Scenario tagging
Categorize real-world incidents for training data
Incident reporting
File structured reports on anomalies and near-misses
What we're looking for
Required
Strong problem-solving instincts and attention to detail under time pressure
Ability to make fast, confident decisions in ambiguous situations
Comfort working with digital dashboards and monitoring interfaces
Clear, structured written communication for documentation and escalation
Sustained focus during monitoring tasks — you notice what drifts
Preferred
Experience in operations, logistics, robotics, or technical support
Familiarity with AI systems, automation tools, or autonomous vehicles
Background in gaming, simulation, or remote system control
Basic technical literacy — you don't need to code, but you read logs comfortably
What success looks like
You can quickly read whether an AI system is confident or confused — and you act on that read without hesitation. Your interventions resolve situations without introducing new problems. Over time, your feedback measurably reduces the frequency of the edge cases you've seen before. You remain calm and decisive in unusual or time-sensitive situations, and your incident documentation is detailed enough that engineers can reproduce and fix what you flagged.
Growth track
01
HITL Operator
02
AI Operations Specialist
03
Autonomous Systems Supervisor
04
AI Safety & Compliance Analyst