Forward Deployed Engineer (FDE) - GenAI / Agentic AI

Tiger Analytics Inc.

1d

About The Position

Tiger Analytics is seeking an experienced, client-facing Forward Deployed Engineer with expertise in Generative AI and the Databricks Data Intelligence Platform. The role partners directly with enterprise clients, engineering teams, and Databricks account teams to turn complex and ambiguous business problems into production-grade data, analytics, AI, and GenAI solutions.

The engineer embeds in customer environments and owns solutions from initial discovery through architecture, implementation, and live deployment. The work includes building scalable Lakehouse data pipelines, modernizing legacy BI and data warehouses, developing AI/ML and GenAI workflows, and improving platform performance and cost. The role also involves leading architectural discussions and connecting Tiger Analytics delivery teams, client stakeholders, and Databricks field engineering teams.

Requirements

• At least 5 years of hands-on experience in Data Engineering or Applied AI/ML Engineering.
• Strong proficiency in Python and SQL.
• Deep hands-on mastery of Apache Spark, including performance tuning, query optimization, cluster sizing, and memory management.
• Proven experience implementing Lakehouse architectures, including Delta Lake, Unity Catalog governance, lineage and access control, and Databricks Workflows.
• Practical experience building and deploying AI/GenAI solutions on Databricks, such as Databricks AI/BI Genie, Mosaic AI, Vector Search, LLM integration, or MLflow.
• Experience migrating enterprise data workloads or modernizing legacy BI/data warehouses onto cloud platforms such as AWS, Azure, or GCP.
• Exceptional communication and consultative skills, with a demonstrated ability to work effectively in fast-paced, client-facing environments.
• Strong customer-facing communication and problem-solving skills.
• Ability to operate independently, navigate ambiguity, and move quickly from problem to solution to production.
• Ability to work effectively with both business and technical stakeholders.

Responsibilities

• Embed with client engineering and business stakeholders to design, build, and deploy end-to-end production solutions on Databricks within accelerated timelines.
• Architect scalable data pipelines using Delta Lake, Unity Catalog, and Apache Spark.
• Support complex 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 using Databricks AI/BI Genie, Mosaic AI, RAG architectures, and Model Serving.
• Lead architectural workshops, translate business requirements into technical roadmaps, and troubleshoot production bottlenecks alongside client teams.
• Act as the primary technical bridge between Tiger Analytics delivery teams, client stakeholders, and Databricks field engineering teams to drive adoption and expand platform capabilities.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Education Level: No Education Listed