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Tech Stack
About the role
- Design and implement AI solution architectures using Vertex AI and Google ADK.
- Develop large-scale data and processing pipelines with Dataproc and BigQuery.
- Create and orchestrate AI workflows using LangChain for conversational and agentic applications.
- Implement semantic search and RAG solutions using Google Vector Database.
- Manage model artifacts and versioning via Artifact Registry.
- Develop prototypes and experiments in Jupyter Notebooks.
- Integrate AI solutions with Google AI Workspace for enterprise applications.
- Establish MLOps best practices and model governance.
- Collaborate with development teams through CI/CD pipelines.
- Document architectures, patterns, and technical guides for the team.
Requirements
- Strong experience with Python for developing AI solutions.
- Advanced knowledge of Vertex AI and Google Cloud Platform tools.
- Experience with LangChain for building applications with LLMs.
- Proficiency in BigQuery for data analysis and processing.
- Familiarity with Jupyter Notebooks for prototyping.
- Knowledge of vector databases and embedding techniques.
Benefits
- We do not tolerate any form of discrimination.
- We encourage everyone to take part in our hiring process, regardless of gender, age, race, or religion.
- A culture of equality.
Applicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills & Tools
PythonVertex AIGoogle Cloud PlatformLangChainBigQueryJupyter Notebookssemantic searchRAG solutionsvector databasesembedding techniques