AI Engineer
通过加入 Sedgwick,你将成为真正有意义的东西的一部分。这是我们33,000名同事每天为世界各地面临意外的事情的人做的事。我们邀请你与我们一起发展自己的职业生涯,体验我们的关心文化,并享受工作和生活平衡。在这里,你能达到什么样的目标没有限制。新闻周刊承认 Sedgwik 是美国最伟大的工作场所的国家顶级公司作为一个伟大的工作地点®财富最佳工作场所在金融服务和保险 AI 工程师首要目的:转型办公室内的 AI 工程师担任企业数据供应链的实践架构师,为组织最先进的分析,数据科学和人工智能倡议提供。该角色执行了高效率,生产级数据提供动力机器学习模型,功能商店和生成人工智能应用程序所需的关键工程工作。作为一个"一天"建设者,Gen AI 工程师设计并交付将传统的本地系统接到包括主体系统,SQL Server 和 DB2等现代云平台的数据管道。该角色确保数据不仅是转移,而且有意设计以满足模型培训,推断和 RAG 基于 AI 系统的统计,性能和治理要求。远程作用,可以访问任何美国州。关键功能和责任 · 设计,构建和维护可靠的 ETL/ELT 管道,这些管道吸收来自本地系统,AWS 服务 (S3,RDS) 和 Azure 平台 (Blob Storage,Azure SQL),集中并策划用于雪和下游人工智能服务中的消费数据。· 开发和维护支持机器学习工作流程的功能存储以及分析优化数据集,确保数据是干净的,版本化的,可复制性的,对数据科学团队具有统计有效性。· 工程师为生成人工智能使用案例提供数据管道,包括自动提取,转换,分碎和将结构化和非结构化数据加载到 AWS 和 Azure 环境中的向量数据库中。·作为 Snowflake 功率用户和技术领导者,实现先进的数据建模模式,雪管自动化,以及计算和存储优化以支持高安全性分析和 AI 工作负荷。·执行非入侵数据提取策略,在压力期间释放了几十年历史旧系统中的关键任务数据
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By joining Sedgwick, you'll be part of something truly meaningful. It’s what our 33,000 colleagues do every day for people around the world who are facing the unexpected. We invite you to grow your career with us, experience our caring culture, and enjoy work-life balance. Here, there’s no limit to what you can achieve.
Newsweek Recognizes Sedgwick as America’s Greatest Workplaces National Top Companies
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AI EngineerPRIMARY PURPOSE: The AI Engineer within the Transformation Office serves as the hands‑on architect of the enterprise data supply chain for the organization’s most advanced analytics, data science, and AI initiatives. This role performs the critical engineering work required to deliver high‑fidelity, production‑grade data that powers machine learning models, feature stores, and generative AI applications.
Operating as a “day‑one” builder, the Gen AI Engineer designs and delivers data pipelines that bridge legacy on‑premise systems—including mainframes, SQL Server, and DB2—with modern cloud platforms such as Snowflake and AWS/Azure AI ecosystems. The role ensures that data is not merely transferred, but deliberately engineered to meet the statistical, performance, and governance requirements of model training, inference, and RAG‑based AI systems.
Remote role, open to any U.S. state.
ESSENTIAL FUNCTIONS AND RESPONSIBILITIES
- Designs, builds, and maintains resilient ETL/ELT pipelines that ingest data from on‑premise systems, AWS services (S3, RDS), and Azure platforms (Blob Storage, Azure SQL), centralizing and curating data for consumption in Snowflake and downstream AI services.
- Develops and maintains feature stores and analytically optimized datasets that support machine learning workflows, ensuring data is clean, versioned, reproducible, and statistically valid for Data Science teams.
- Engineers data pipelines that enable generative AI use cases, including the automated extraction, transformation, chunking, and loading of structured and unstructured data into vector databases across AWS and Azure environments.
- Acts as a Snowflake power user and technical lead, implementing advanced data modeling patterns, Snowpipe automation, and compute and storage optimization to support high‑concurrency analytics and AI workloads.
- Executes non‑invasive data extraction strategies to unlock mission‑critical data from decades‑old legacy systems while preserving system stability and avoiding disruption to core business operations.
- Designs and manages complex, cross‑platform data workflows using orchestration tools such as Airflow, AWS Step Functions, and Azure Data Factory to ensure reliable, synchronized data movement across the organization’s multi‑cloud architecture.
- Partners closely with central IT, database administrators, infrastructure, and security teams to resolve connectivity and access challenges—including PrivateLink, IAM, network segmentation, and firewall controls—while securing production approval for new data integrations.
- Implements automated data quality, validation, and observability frameworks to detect data drift, anomalies, and integrity issues that could negatively impact production analytics, machine learning, or AI systems.
- Drives efficiency across the data ecosystem by optimizing storage, compute usage, and query performance in Snowflake, AWS, and Azure, ensuring responsible cost management and measurable ROI for Transformation Office initiatives.
- Operates as a dedicated engineering partner to MLOps, Data Science, and AI teams, rapidly iterating on evolving data requirements and translating experimental use cases into scalable, production‑ready data solutions.
ADDITIONAL FUNCTIONS and RESPONSIBILITIES
- Performs other duties as assigned.
- Travel as required.
QUALIFICATIONS
Education & Licensing
Master’s degree in Computer Science, Data Engineering, or a related field from an accredited college or university preferred.
Experience
Six (6) years of hands-on data engineering experience, with a track record of building production-grade pipelines for Data Science and AI in multi-cloud environments or equivalent combination of education and experience required.
Skills & Knowledge
- Expert-level proficiency in Snowflake architecture, including data sharing, performance tuning, and the integration of Snowflake with external cloud AI services
- Advanced, hands-on knowledge of AWS (S3, Glue, Lambda) and Azure (Data Factory, Synapse) data services
- Mastery of Python, SQL, and PySpark. Deep experience with data orchestration and containerization (Docker)
- Proven ability to interface with "old world" tech (on-premise SQL, Mainframe extracts, flat files) and transform it for modern cloud consumption
- A strong understanding of the specific data needs for Machine Learning (feature engineering) and Generative AI (vectorization and embedding pipelines)
- A "get-it-done" attitude, capable of navigating enterprise bureaucracy and technical debt to ship code at the speed required by a Transformation Office
- Ability to work in a team environment
- Ability to meet or exceed Performance Competencies
WORK ENVIRONMENT
When applicable and appropriate, consideration will be given to reasonable accommodations.
Mental: Clear and conceptual thinking ability; excellent judgment, troubleshooting, problem solving, analysis, and discretion; ability to handle work-related stress; ability to handle multiple priorities simultaneously; and ability to meet deadlines
Physical: Computer keyboarding, travel as required
Auditory/Visual: Hearing, vision and talking
The statements contained in this document are intended to describe the general nature and level of work being performed by a colleague assigned to this description. They are not intended to constitute a comprehensive list of functions, duties, or local variances. Management retains the discretion to add or to change the duties of the position at any time.
Sedgwick is an Equal Opportunity Employer and a Drug-Free Workplace.
If you're excited about this role but your experience doesn't align perfectly with every qualification in the job description, consider applying for it anyway! Sedgwick is building a diverse, equitable, and inclusive workplace and recognizes that each person possesses a unique combination of skills, knowledge, and experience. You may be just the right candidate for this or other roles.
Originally posted on Himalayas