Forward Deployed Engineer (FDE) - GenAI / Agentic AI
New
T
Tiger AnalyticsAI analytics
Workable workplace: remote; Workable locations: Canada. United StatesFull-TimeSenior
Salary not disclosed
Apply NowOpens the employer's application page
Job Details
- Experience
- 5+ years of hands-on experience in Data Engineering, Applied AI/ML Engineering
- Required Skills
- PythonSQLMLFlowSparkDatabricks
Requirements
- Have 5+ years of hands-on experience in Data Engineering or Applied AI/ML Engineering.
- Demonstrate strong proficiency in Python and SQL.
- Have deep hands-on mastery of Apache Spark, including performance tuning, query optimization, cluster sizing, and memory management.
- Have experience implementing Lakehouse architectures, including Delta Lake, Unity Catalog, and Databricks Workflows.
- Understand Unity Catalog governance, lineage, and access control.
- Have practical experience building and deploying AI/GenAI solutions on Databricks, such as Databricks AI/BI Genie, Mosaic AI, Vector Search, LLM integration, or MLflow.
- Have experience migrating enterprise data workloads or modernizing legacy BI/data warehouses onto AWS, Azure, or GCP.
- Be effective in fast-paced, client-facing environments and able to work with business and technical stakeholders.
- Be comfortable operating independently, navigating ambiguity, and moving from problem to production.
Responsibilities
- Embed with client engineering and business stakeholders to design, build, and deploy end-to-end production solutions on Databricks.
- Architect scalable data pipelines using Delta Lake, Unity Catalog, and Apache Spark.
- Handle cloud migrations, legacy BI modernization, and performance and cost optimization.
- Build and deploy enterprise AI/ML workflows, knowledge layers and ontologies, and natural-language analytics solutions.
- Use Databricks AI/BI Genie, Mosaic AI, RAG architectures, and Model Serving to deliver AI and analytics solutions.
- Lead architectural workshops and translate business requirements into technical roadmaps.
- Troubleshoot production bottlenecks alongside client teams.
- Bridge Tiger Analytics delivery teams, client stakeholders, and Databricks field engineering teams to drive adoption and expand platform capabilities.
View Full Description & ApplyYou'll be redirected to the employer's site
