出海雷达

资深AI软件开发工程师

Principal AI Software Developer

AI开发工程限定地区(需当地身份)
公司Pyramid Systems, Inc.
薪资$166,091 - $210,000/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Other
发布时间18 天前
数据来源Himalayas
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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。

Overview
高级首席全栈AI工程师作为一位资深、亲自参与的全栈AI工程师,负责设计、开发和交付支持AIR平台的大规模关键任务AI系统。该职位结合高级技术领导力、在现代云架构(Next.js、Terraform、GitHub、AWS、Azure和GCP)上构建的AI和LLM系统的实际专业知识,以及对企业架构、治理和创新的责任。这是Nexus为Pyramid Systems提供的全职职位。
Responsibilities

  • 作为高级技术负责人,与总监合作并在其指导下定义AIR平台的AI和应用架构
  • 制定与任务成果、合规性和可扩展性一致的企业现代化路线图
  • 领导分布式、云原生和混合AI系统的架构
  • 定义并执行参考架构、标准和可重用框架
  • 推动跨项目的技术决策,确保互操作性、安全性和长期可持续性
  • 领导先进AI解决方案的设计、开发和部署,包括大型语言模型(LLMs)和基础模型、检索增强生成(RAG)系统、代理工作流和编排框架
  • 使用Next.js、云原生API和AWS、Azure、GCP上的托管AI服务构建可扩展的AI应用程序和服务
  • 从用户界面到后端服务、API和数据层,端到端构建全栈AI应用程序
  • 通过API、中间件和事件驱动模式将AI和LLM功能集成到现有企业应用程序和遗留平台(如内容管理系统、案件管理系统和记录系统)中
  • 监督完整的AI解决方案生命周期:数据管道、评估、部署和监控
  • 推动LLM性能和成本优化(例如缓存、提示和上下文优化、模型选择)
  • 建立强大的MLOps实践,利用基于GitHub的自动化、CI/CD流水线和工具
  • 搭建企业CI/CD到AI/MLOps的流水线,从时间限定的概念验证和最小可行产品(MVP)实现开始,逐步成熟为生产系统
  • 在联邦AI政策(例如NIST AI RMF、OMB M-25-21和M-25-22、行政命令14179)方面担任专家
  • 定义并实施负责任AI框架,包括模型验证和评估、偏差缓解等
查看英文原文

Overview
The Senior Principal Full Stack AI Engineer serves as a senior, hands-on full-stack AI engineer, leading the design, development, and delivery of large-scale mission-critical AI systems supporting the AIR Platform. This role combines senior technical leadership, hands-on expertise in AI and LLM systems built on a modern cloud stack (Next.js, Terraform, GitHub, AWS, Azure, and GCP), and ownership of enterprise architecture, governance, and innovation. This is a full-time position under Nexus for Pyramid Systems.
Responsibilities

  • Serve as a senior technical lead, defining AI and application architecture for the AIR Platform in partnership with and under the direction of the Director
  • Establish enterprise modernization roadmaps aligned to mission outcomes, compliance, and scalability
  • Lead architecture for distributed, cloud-native, and hybrid AI systems
  • Define and enforce reference architectures, standards, and reusable frameworks
  • Drive cross-program technical decision-making to ensure interoperability, security, and long-term sustainability
  • Lead design, development, and deployment of advanced AI solutions, including large language models (LLMs) and foundation models, Retrieval-Augmented Generation (RAG) systems, agentic workflows, and orchestration frameworks
  • Architect and implement scalable AI applications and services using Next.js, cloud-native APIs, and managed AI services across AWS, Azure, and GCP
  • Build full-stack AI applications end to end, from user-facing interfaces to back-end services, APIs, and data layers
  • Integrate AI and LLM capabilities into existing enterprise applications and legacy platforms (e.g., content management, case management, and records systems) via APIs, middleware, and event-driven patterns
  • Oversee the full AI solution lifecycle: data pipelines, evaluation, deployment, and monitoring
  • Drive LLM performance and cost optimization (e.g., caching, prompt and context optimization, model selection)
  • Establish robust MLOps practices leveraging GitHub-based automation, CI/CD pipelines, and tooling
  • Stand up the enterprise CI/CD-to-AI/MLOps pipeline, beginning with time-boxed proofs of concept and MVP implementations that mature into production systems
  • Serve as subject matter expert in federal AI policy (e.g., NIST AI RMF, OMB M-25-21 and M-25-22, Executive Order 14179)
  • Define and operationalize Responsible AI frameworks, including model validation and evaluation, bias mitigation and fairness, and explainability, auditability, and safety
  • Ensure compliance with FISMA, FedRAMP, NIST 800-53, privacy, and Section 508 requirements
  • Lead large-scale modernization initiatives (e.g., legacy-to-cloud, microservices transformation, including refactoring and re-platforming efforts)
  • Define repeatable modernization frameworks and accelerators
  • Oversee DevSecOps pipelines and CI/CD automation (e.g., GitHub Actions), zero-trust architectures, and secure software supply chain practices
  • Ensure delivery of resilient, high-availability systems in regulated federal environments
  • Lead multiple concurrent engineering efforts across integrated teams
  • Provide technical leadership to architects, engineers, and DevSecOps specialists, including establishing coding standards and engineering best practices
  • Mentor senior engineers and technical leaders; elevate engineering excellence and code quality
  • Support technical strategy in proposals, captures, and client engagements
  • Contribute to thought leadership (whitepapers, architecture patterns, platform strategy)
  • Expert-level proficiency across the platform stack (Next.js, Terraform, GitHub, AWS, Azure, and GCP), including building large-scale AI applications, APIs, and data pipelines
  • Full-stack engineering skills, including modern front-end frameworks (e.g., Next.js/React), back-end services, RESTful APIs, microservices, and cloud-native deployment (e.g., containers, Kubernetes)
  • Deep expertise in LLMs and generative AI, including transformer-based model architectures and their practical application
  • Proven ability to integrate AI capabilities into existing and legacy enterprise systems (e.g., legacy CMS or COTS platforms) using APIs, middleware, connectors, and event-driven architectures
  • Strong understanding of large-scale data systems and ML evaluation methodologies
  • Experience working with sensitive data, including PII safeguards such as anonymization, masking, and data loss prevention
  • Experience with enterprise integration technologies, including REST/SOAP services, message queues, ETL pipelines, and SQL/NoSQL databases
  • Expertise designing AI systems in cloud-native, distributed environments across AWS, Azure, and GCP
  • Proficiency with infrastructure as code, including Terraform, for provisioning and managing cloud environments
  • Proficiency with managed generative AI services (e.g., AWS Bedrock, Azure OpenAI Service, Google Vertex AI) and integrating frontier models such as GPT, Claude, and Gemini
  • Hands-on experience with LLM application stacks, including orchestration frameworks (e.g., LangChain, LlamaIndex, Semantic Kernel), embeddings, vector databases, and prompt engineering
  • Executive communication skills with experience influencing senior leaders
  • Demonstrated ability to own solutions end to end, from discovery and prototyping through production deployment, integration, and ongoing support
  • Ability to balance strategic vision with deep hands-on technical execution

Qualifications

  • U.S. Citizenship required
  • Bachelor’s or Master’s degree in Computer Science, Engineering, or related field
  • 12–15+ years of software engineering experience, including significant leadership responsibility
  • 8+ years of applied AI/ML experience, including building and deploying production systems (LLMs, generative AI, and large-scale or distributed model systems) Expert-level full-stack development experience, including designing production-grade AI systems, data pipelines, and microservices-based architectures
  • Deep experience with cloud platforms (Azure, AWS, GCP), including FedRAMP environments
  • Hands-on experience building full-stack applications with Next.js and managing infrastructure as code with Terraform
  • Experience with AI platforms and architectures (e.g., AWS Bedrock, Azure OpenAI Service, Google Vertex AI, RAG, agents)
  • Proven success delivering enterprise-scale systems and modernization programs
  • Strong background in microservices, APIs, distributed systems, and DevSecOps practices
  • Demonstrated ability to translate AI research into production systems
  • Active clearance (Public Trust, Secret, or higher) preferred
  • Startup or early-stage company experience preferred
  • Experience using AI coding tools (e.g., Claude Code, OpenAI Codex) to accelerate development preferred

Target Pay Range
The below listed pay range for this position is not a guarantee of compensation or salary. The final offered salary will be influenced by a host of factors including, but not limited to, geographic location, Federal Government contract labor categories and contract wage rates, relevant prior work experience, specific skills and competencies, education, and certifications. Our employees value the flexibility at Pyramid Systems that allows them to balance quality work and their personal lives. We offer competitive compensation, benefits, to include our Employee Stock Ownership Program, FlexPTO, and learning and development opportunities.Pyramid Min
USD $166,091.00/Yr.Pyramid Max
USD $210,000.00/Yr.Why Pyramid?
Pyramid Systems, Inc. is an award-winning, technology leader, driving digital transformation across federal agencies. We empower forward-thinking innovations, accelerate production-ready software, and deliver secure solutions so federal agencies can meet their mission goals. Voted a Top Workplace, both regionally (Washington, DC) and Nationally (USA) the past 2 years (2023 and 2024) based on the feedback from our employees, we are headquartered in Fairfax, VA. and have a growing national footprint. We value and promote our Flexible Workplace approach because of the positive impacts it has on work-life integration. We remain committed to ensuring every employee’s voice is heard, performance and results are recognized and rewarded, development and advancement is a focus, and diversity, equity and inclusion is a company priority. We offer competitive compensation and benefits (including a recently launched Employee Stock Ownership Plan - ESOP), a robust performance-based rewards program, and we know how to have fun! Our people and culture have endured and delivered for our clients for nearly three decades.EEO Statement
Pyramid Systems, Inc. is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, or protected veteran status and will not be discriminated against on the basis of disability.Originally posted on Himalayas

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