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Test Databricks data pipelines with SQL at YASH Technologies. The role calls for ETL testing experience and a foundational understanding of Databricks.
Atvērt
Oyster ir personāla tehnoloģiju uzņēmums, kas palīdz uzņēmumiem pieņemt darbā un pārvaldīt starptautiskos darbiniekus un līgumdarbiniekus. Tā globālā nodarbinātības platforma apvieno algu aprēķinu, atbilstību normatīvo aktu prasībām, darbinieku labumu administrēšanu un talantu mobilitātes atbalstu, palīdzot organizācijām orientēties vietējās nodarbinātības prasībās, paplašinoties pāri robežām. Oyster apvieno automatizētas darbplūsmas ar vietējām zināšanām, lai vienkāršotu darbinieku uzņemšanu un pastāvīgu darbaspēka pārvaldību vairāk nekā 180 valstīs.
Senior AI Platform Data Engineer — Remote in the United Kingdom
Build secure data pipelines and reusable AI platform infrastructure for Oyster’s global employment platform. Support LLM, RAG, vector search, and production AI capabilities.
Apraksts
- Create data pipelines and platform capabilities that power AI applications, knowledge systems, and AI workflows
- Develop and operate pipelines for ingestion, transformation, chunking, embeddings, retrieval, vector search, metadata, and knowledge management
- Provide secure, reusable access to enterprise data and systems through APIs, MCP, tool calling, and related patterns
- Create reusable services, libraries, frameworks, and developer tools that bring AI capabilities into production
- Apply sound practices for data modeling, quality, lineage, access, reliability, and governance across AI data and systems
- Define approaches for AI deployment, observability, evaluation, and lifecycle management
- Work with Engineering, Product, IT, and other stakeholders to turn AI concepts into scalable production systems
- Ensure AI platform capabilities satisfy security, privacy, access-control, and data-governance standards
- Assess emerging AI and data technologies for their potential value to Oyster
Prasības
- At least five years of experience in data engineering, platform engineering, backend engineering, ML engineering, or a related field
- Experience building and operating production systems
- Advanced Python and SQL skills
- Strong grounding in data engineering, including pipelines, modeling, quality, orchestration, and secure data access
- Experience with Snowflake, Databricks, or a comparable modern data platform
- Experience using dbt, Airflow, or similar tools
- Hands-on experience building or supporting production systems that use LLMs or generative AI
- Practical experience with one or more of RAG, embeddings, vector search, tool or function calling, AI agents, and enterprise knowledge systems
- Experience delivering reusable data or platform capabilities for multiple teams
- Experience moving systems from experimentation into dependable production, with attention to scalability, observability, performance, and maintainability
- Knowledge of security, authentication and authorization, privacy, and data governance
- Ability to collaborate across Engineering, Product, and IT on ambiguous AI and data challenges
- Reliable home internet access or the ability to obtain it
- Fluent English proficiency
- Based within UTC-6 to UTC+3
- Authorized to work in the country where you live
- Bonus: experience with AWS Bedrock or another managed foundation-model platform
- Bonus: experience with MCP or comparable approaches
- Bonus: experience with LLM evaluation, observability, monitoring, or AI quality
- Bonus: experience with LangChain, LangGraph, vector databases, search technologies, AI security, governance, responsible AI, internal developer platforms, SDKs, APIs, reusable infrastructure, or data, AI, and ML platform environments
Priekšrocības
- 40 days of annual leave, including holidays and vacation, or more where required by local law
- Access to the Plumm mental well-being service
- Monthly well-being allowance through the ThanksBen wallet
- At least three months of paid parental leave for every new parent
- Job protection for up to 12 months or the locally required period
- Work-from-home stipend for a laptop and home-office equipment
- Fully remote work from home
- Flexible, asynchronous, collaborative working arrangements
- Inclusive and globally distributed work environment
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