出海雷达

资深工程师,AI运营与治理,工作场所AI(R5428)

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

AI开发工程职能支持限定地区(需当地身份)
公司Shield AI
薪资$200,000 - $300,000/年
工作地点United States
地域资格限定地区(需当地身份)
时区要求日间重叠约 9 小时,基本正常作息
用工类型Full Time
发布时间13 天前
数据来源Himalayas
前往 Himalayas 查看并投递 →
注意地域限制:该职位明确限定在 United States 招聘。如果你是位于中国大陆的求职者,通常需要当地工作身份才能投递,或需与雇主确认是否接受独立合同(Contractor)形式合作。

Shield AI 是一家由风险投资支持的国防科技公司,使命是通过智能系统保护现役军人和平民。其产品包括 Hivemind 自主软件、V-BAT 和 X-BAT 飞机,以及 Aechelon 模拟和合成现实技术。Shield AI 在美国、欧洲、中东和亚太地区设有办公室和设施,其技术在全球范围内积极支持作战行动。如需更多信息,请访问 www.shield.ai。关注 Shield AI 的 LinkedIn、X、Instagram 和 YouTube 账号。
这是一个深度技术的个人贡献者职位,向企业 AI 头脑风暴与治理主管汇报。该职位将负责工作场所 AI 的重要技术运营负载:平台配置、连接器和集成管理、可观测性布线、密钥和访问规范,以及生产环境中的实际更改。

同时,该职位将帮助将生产实际情况转化为治理文档、风险评估、状态更新和培训/赋能支持——为负责人提供一个能够在技术层和“更软性”层面上运作的助力者。

该职位还将作为工作场所 AI 事件和生产问题的现场技术响应者。高级工程师需要调查故障,跨平台、集成、提示、配置和访问路径进行排查,适当实施缓解或修复措施,并帮助快速恢复服务,同时记录根本原因、经验教训和预防步骤。
主要职责:
· 实施和维护 AI 平台配置
在主管指导下,负责 AI 平台和编排工具(模型、路由、防护机制、租户、策略、角色映射、提示库等)的日常配置。
· 管理连接器、集成和数据访问路径
设计、配置和维护到 SaaS 系统、数据源和工作流工具的连接器和扩展;确保连接可靠、安全,并符合访问策略。
· 负责 AI 工具的可观测性布线
设置和维护 AI 工作流和工具的日志、指标和警报;确保关键信号(延迟、错误、使用情况、漂移指标)被捕捉并可见于团队。
· 管理密钥和访问规范
实现 API 密钥、令牌和凭证的安全存储和轮换;维护访问控制配置

查看英文原文

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.
This is a deeply technical individual contributor role reporting to the Head of AI Operations & Governance (Enterprise AI). This person will own significant portions of the technical operating load for workplace AI: platform configuration, connector and integration management, observability wiring, secrets and access hygiene, model/prompt lifecycle mechanics, and hands-on changes in production.

At the same time, the role will help translate production realities into governance artifacts, risk assessments, status updates, and training/enablement support — giving the Head a force multiplier who can operate at both the technical and “softer” layers of AI operations and governance.

This role will also serve as a hands-on technical responder for workplace AI incidents and production issues. The Staff Engineer is expected to investigate failures, troubleshoot across platforms, integrations, prompts, configurations, and access paths, implement mitigations or fixes where appropriate, and help restore service quickly while documenting root cause, lessons learned, and prevention steps.
Key responsibilities:
· Implement and maintain AI platform configurations
Own day-to-day configuration of AI platforms and orchestration tools (models, routes, guardrails, tenants, policies, role mappings, prompt libraries, etc.), under the direction of the Head.
· Manage connectors, integrations, and data access paths
Design, configure, and maintain connectors and extensions into SaaS systems, data sources, and workflow tools; ensure connectivity is reliable, secure, and aligned with access policies.
· Own observability wiring for AI tools
Set up and maintain logging, metrics, and alerts for AI workflows and tools; make sure key signals (latency, errors, usage, drift indicators) are captured and visible to the team.
· Handle secrets and access hygiene
Implement secure storage and rotation for API keys, tokens, and credentials; maintain access control configurations and partner with Security/IT on reviews and remediation.
· Execute model and configuration changes in production
Implement model swaps, policy updates, prompt changes, version upgrades, and rollout plans based on decisions made by the Head; maintain detailed change records and rollback paths.
· Support technical evaluations and benchmarking
Run experiments and benchmarks on models, tools, and configurations; collect and summarize technical performance data to inform governance and roadmap decisions.
· Translate technical signals into governance and risk views
Help the Head interpret logs, metrics, and incidents into clear risk, reliability, and compliance narratives that can be shared with Security, Legal, HR, and business sponsors.
· Contribute to playbooks and training
Co-author technical sections of operational playbooks, runbooks, and training materials; occasionally participate in training or office hours to help users understand capabilities and guardrails.
· Coordinate and communicate on incidents and changes
Act as a technical point of contact in incidents: triage, investigate, propose mitigations, execute fixes, and document learnings; communicate clearly with non-technical stakeholders when needed.
Required qualifications:
· 4–7+ years in roles such as platform engineer, DevOps/SRE, ML/AI operations, or technical SaaS operations, with hands-on responsibility for production systems.
· Strong fluency in APIs, integrations, and infrastructure-as-config concepts; able to work in code/JSON/YAML configuration environments and with automation where appropriate.
· Hands-on experience with monitoring and observability tools (logs, metrics, alerts) and using them to diagnose issues and guide improvements.
· Practical experience working with at least one class of AI or automation platforms (LLM providers, AI productivity tools, RPA/workflow engines, or similar).
· Comfort with secure secrets management and access control practices (roles, permissions, key rotation, least-privilege patterns).
· Ability to document technical work and decisions clearly for both technical and non-technical audiences.
· Strong ownership mindset, bias to action, and comfort operating close to production in a high-stakes environment.
Preferred qualifications:
· Experience in ML/AI ops specifically (model deployment, evaluation, drift monitoring), even if not as a dedicated ML engineer.
· Familiarity with prompt engineering, policies/guardrails, and configuration patterns 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 and mitigation.
· Prior involvement in incident response, change management, or on-call rotations for critical systems.
#LC

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.
###

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

本页面信息整理自 Himalayas,版权归原发布方所有。职位可能随时关闭,投递请以原始页面为准。 本站只做信息聚合展示,不参与招聘流程,也不向求职者收取任何费用。

该公司其他在招职位

资深解决方案工程师

Shield AIUnited States$180,000 - $270,000/年Full Time5 天前
开发工程市场运营限定地区(需当地身份)

← 返回全部职位