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Staff Engineer, AI Operations & Governance, Workplace AI (R5428)

Shield AIRemoteEnterprise Operations
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Salary
Not listed
Job type
Full Time Employee
Work mode
Remote
Experience
Senior · 8+ yrs
Posted
22 Sept 2026
Status
Open · checked 9d ago

About this role

Shield AI is hiring a remote, full-time Staff Engineer for AI Operations & Governance to manage workplace AI systems and support enterprise reliability. This individual contributor role suits an experienced engineer with a strong background in platform operations, infrastructure configuration, and technical risk management.

Role Overview

The Staff Engineer handles the technical operating load for workplace AI at Shield AI. Responsibilities include platform configuration, connector management, observability, access hygiene, and production changes. The position bridges technical execution with governance requirements, acting as a responder for production incidents and translating technical data into risk assessments.

Key Responsibilities

Implement and maintain AI platform configurations, including models, routes, guardrails, and role mappings.
Manage connectors, integrations, and secure data access paths into SaaS systems and workflow tools.
Set up logging, metrics, and alerts to monitor latency, errors, usage, and drift indicators.
Handle secure storage, rotation, and access control for API keys, tokens, and credentials.
Execute model swaps, policy updates, prompt changes, and rollouts in production environments.
Run experiments and benchmarks to collect performance data for governance and roadmap decisions.
Translate technical logs, metrics, and incidents into risk and compliance narratives for various stakeholders.
Co-author technical sections of operational playbooks, runbooks, and training materials.
Act as a technical point of contact during incidents to investigate, mitigate, and document root causes.

Requirements

Minimum of 8 years in platform engineering, DevOps/SRE, ML/AI operations, or technical SaaS operations.
Fluency in APIs, integrations, and infrastructure-as-config concepts using code, JSON, or YAML.
Hands-on experience with monitoring, observability tools, logs, metrics, and alerts.
Practical experience with LLM providers, AI productivity tools, RPA, or workflow engines.
Familiarity with secure secrets management and access control practices.
Ability to document technical work clearly for both technical and non-technical audiences.

Nice to Have

Specific experience in ML/AI operations covering model deployment, evaluation, and drift monitoring.
Familiarity with prompt engineering, policies, and guardrails for LLM-based systems.
Exposure to governance, compliance, or risk frameworks for data-driven or AI systems.
Experience collaborating with Security, Legal, and business stakeholders on technical risk.
Prior involvement in incident response, change management, or on-call rotations for critical systems.

Skills and Tools

APIs and integrations
Infrastructure-as-config (JSON, YAML)
Monitoring and observability tools
AI and automation platforms (LLM providers, RPA, workflow engines)
Secrets management and access control systems

Salary and Benefits

Full-time employee offer package includes pay within the listed range, bonus, benefits, and equity.
Compensation is influenced by skill set, experience level, licenses, certifications, and work location.
Offers are contingent on a cleared background and possible reference check.

About the Company

Shield AI is a venture-backed defense-tech company focused on protecting service members and civilians through intelligent systems. Its technology portfolio includes Hivemind autonomy software, V-BAT and X-BAT aircraft, and Aechelon simulation and synthetic reality technologies. The organization maintains offices and facilities across the U.S., Europe, the Middle East, and Asia-Pacific.

How to Apply

Interested candidates should visit the official Shield AI careers page to submit an application.

Skills and tech stack

APIsJSONYAMLLLM providersRPAWorkflow enginesLLMPrompt Engineering

Questions candidates ask

What is the location for this role?

This position is remote.

How many years of experience are required?

The role requires 8+ years of experience in platform engineering, DevOps/SRE, ML/AI operations, or technical SaaS operations.

Is this a management or individual contributor position?

This is a deeply technical individual contributor role.

What components are included in the full-time employee offer package?

The full-time package includes pay within the listed range, a bonus, benefits, and equity.

Who does this position report to?

The role reports directly to the Head of AI Operations & Governance (Enterprise AI).

Ready to apply?

The application is on the official Shield AI careers page.

Apply on company site