Job Overview
Location
San Francisco
Job Type
Full-time
Category
Engineering
Date Posted
July 14, 2026
Full Job Description
📋 Description
- • Company Background: Specter's mission is to help automate the physical world. They build video sensors with state-of-the-art AI agents that answer any question, anywhere in their environments.
- • The Role: The Fleet Reliability Engineer will own the fleet's reliability data pipeline end to end, drive down observability cost, and instrument the fleet and own the health metrics that measure reliability.
- • RESPONSIBILITIES:
- • Reliability Data Platform — Primary: Own the fleet's reliability data pipeline end to end, drive down observability cost, instrument the fleet, and own the health metrics that measure reliability.
- • Proof-of-Recovery & Alert Hygiene: Verify that fixes hold fleet-wide, cut alert noise at the source, and turn repeat failure patterns into automated detection and recovery.
- • Fleet Health & Failure-Mode Analytics: Turn fleet telemetry into a live picture of which cohorts, hardware revisions, and firmware versions are trending toward failure, and why.
- • Reliability Economics & Prioritization: Score reliability work in dollars, set and track the fleet's reliability targets, and give the team the data to make reliability-versus-cost tradeoffs.
- • QUALIFICATIONS:
- • Strong data and software skills — Python (or Go) and SQL — and the ability to own a data pipeline end to end.
- • Hands-on building and tuning observability stacks (OpenTelemetry, Grafana, Prometheus, Datadog, or similar), including their cost.
- • Experience operating physical or embedded device fleets at scale, and reasoning about how hardware fails in the field.
- • Comfortable turning messy field telemetry into trends, failure modes, and forecasts.
- • Fluency with databases and data modeling (PostgreSQL or equivalent); infrastructure-as-code familiarity (Terraform or similar) a plus.
- • Bias toward building mechanisms over doing manual work.
- • Nice to have: reliability/SRE fundamentals (SLOs, error budgets, proof-of-recovery) applied to a physical fleet.
- • Nice to have: experience across the hardware-software boundary — power, connectivity, and physical failure modes.
🎯 Requirements
- • Strong data and software skills — Python (or Go) and SQL — and the ability to own a data pipeline end to end.
- • Hands-on building and tuning observability stacks (OpenTelemetry, Grafana, Prometheus, Datadog, or similar), including their cost.
- • Experience operating physical or embedded device fleets at scale, and reasoning about how hardware fails in the field.
- • Comfortable turning messy field telemetry into trends, failure modes, and forecasts.
- • Fluency with databases and data modeling (PostgreSQL or equivalent); infrastructure-as-code familiarity (Terraform or similar) a plus.
🏖️ Benefits
- • Competitive salary and benefits package.
- • Opportunity to work with a fast-growing team and contribute to the development of cutting-edge technology.
- • Collaborative and dynamic work environment.
- • Professional development and growth opportunities.
Skills & Technologies
See exactly how your profile matches this role — strengths, skill gaps, and what to do about them.
About Specter Inc.
Specter is a cybersecurity company focused on providing advanced threat detection and response solutions. Their platform leverages artificial intelligence and machine learning to identify and neutralize sophisticated cyber threats in real-time. Specter's technology is designed to protect organizations from a wide range of attacks, including malware, ransomware, and advanced persistent threats. They offer services such as continuous monitoring, incident response, and security analytics, enabling businesses to enhance their security posture and minimize risks. The company serves various industries, including finance, healthcare, and technology, by delivering robust and scalable cybersecurity solutions.
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