Senior Staff Lead Site Reliability Engineer (R5803)

Shield AI; San Diego (CA); On-site; USD 190,000 - 280,000; Full time

Job summary

Shield AI in San Diego, CA seeks an experienced SRE Lead to establish and mature reliability practices across our cloud infrastructure and platform services.

You will define reliability targets, improve observability, and ensure production systems operate predictably, while mentoring teams in a reliability-first mindset.

Qualifications

• 7+ years in SRE, software or infrastructure engineering.
• Experience with AWS or major cloud, IaC, and incident response.
• Strong ability to diagnose complex failures across systems.

Responsibilities

• Define SLIs/SLOs and measure service reliability.
• Lead incident response and root-cause analysis.
• Improve monitoring, logging, tracing and automation.
• Mentor engineers and guide reliability practices.

Skills

SRE leadership

Reliability engineering

Cloud engineering

Python/Go scripting

AWS

Kubernetes

Incident response

Tools

Terraform

Kubernetes

Docker

AWS

Job description

Shield AI is a venture-backed defense-tech company with the mission of protecting service members and civilians with intelligent systems. Its products include Hivemind autonomy software, V-BAT and X-BAT aircraft, and Aechelon simulation and synthetic reality technologies. With offices and facilities across the U.S., Europe, the Middle East, and Asia-Pacific, Shield AI’s technology actively supports operations worldwide. For more information, visit www.shield.ai . Follow Shield AI on LinkedIn , X , Instagram , and YouTube .

Job Description:

Hivemind is looking for an experienced SRE lead to help drive the establishment of our SRE function.

As the SRE Lead, you will establish and mature the reliability practices used across our cloud infrastructure and platform services. You will work with Cloud Engineering and product teams to define reliability targets, improve observability, and ensure that production systems can be operated and recovered predictably.

This is a deeply technical, hands-on role. You will investigate complex failures, improve the systems and tooling used to operate our platforms, and turn lessons from incidents into engineering improvements. You will provide technical leadership for reliability engineering, helping teams adopt practices that improve system health without adding unnecessary process.

You will act as a thought-leader and mentor within the Cloud Engineering and Reliability teams to level up teammates and encourage building with a reliability-first mindset.

What You'll Do:

• Define and implement SLIs, SLOs, and other measures of service reliability
• Build and improve monitoring, alerting, logging, and tracing for infrastructure and platform services
• Lead technical response to complex incidents and drive root-cause analysis through resolution
• Identify recurring failure modes and work with engineering teams to eliminate them
• Improve system resilience through automation, testing, capacity planning, and failure recovery
• Develop tooling and automation that reduces manual operational work
• Partner with product and platform teams to incorporate reliability requirements into system design
• Establish incident response practices that improve detection, diagnosis, communication, and recovery
• Mentor product engineers and drive adoption of strong reliability and operational practices
• Mentor teammates in SRE and Cloud Engineering
• Define and manage short-and-long term SRE roadmap, distributing work across teammates

Required Qualifications:

• 7+ years of experience in SRE, software engineering, infrastructure engineering, or related fields
• Experience operating production services with defined availability and reliability requirements
• Experience implementing SLIs, SLOs, monitoring, alerting and incident response practices
• Experience designing and operating infrastructure in AWS or another major cloud environment
• Experience with infrastructure-as-code and automated infrastructure provisioning
• Experience supporting containerized applications and distributed systems
• Experience developing operational tooling or automation using Python, Go, or a similar language
• Ability to diagnose complex failures across applications, infrastructure, networking, and dependent services
• Experience leading incident response and root-cause analysis across engineering teams
• Experience leading and executing on technical vision of a team over multi-quarter timelines

Preferred Qualifications:

• Experience establishing or maturing an SRE function within an engineering organization
• Experience with Kubernetes and cloud-native observability systems
• Experience operating systems in regulated or compliance-driven environments
• Experience with capacity planning, performance analysis, and cloud cost management
• Background supporting shared infrastructure across multiple products or engineering organizations
• Experience with building roadmaps in ticketing systems
• Experience acting as a mentor for other engineers

$190,000 - $280,000 a year

Full-time regular employee offer package:

Pay within range listed + Bonus + Benefits + Equity

Temporary employee offer package:

Pay within range listed above + temporary benefits package (applicable after 60 days of employment)

Salary compensation is influenced by a wide array of factors including but not limited to skill set, level of experience, licenses and certifications, and specific work location. All offers are contingent on a cleared background and possible reference check. Military fellows and part-time employees are not eligible for benefits. Please speak to your talent acquisition representative for more information.

If you have a disability or special need that requires accommodation, please let us know.

Shield AI is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, marital status, disability, gender identity or Veteran status.

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.