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Tiger Analytics

Delivers Data and AI transformation

Forward Deployed Engineer - GenAI, Agentic AI

AI Application EngineeringPosted on Nov 13
Full-timeRemote in CanadaNo salary listedRemote

About the Job

Requirements

  • At least 5 years of hands-on experience in Data Engineering or Applied AI/ML Engineering.
  • Strong proficiency in Python and SQL, with 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, large language model integration, or MLflow.
  • Experience migrating enterprise data workloads or modernizing legacy business intelligence/data warehouses onto AWS, Azure, or Google Cloud Platform.
  • Strong customer-facing communication and problem-solving skills, and a demonstrated ability to operate effectively in fast-paced client-facing environments.
  • Ability to operate independently, navigate ambiguity, and move quickly from problem to solution and 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; handle complex cloud migrations, legacy business intelligence 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, retrieval-augmented generation architectures, and Model Serving.
  • Lead architectural workshops, translate business requirements into technical roadmaps, and troubleshoot production bottlenecks alongside client teams.
  • Serve as the primary technical bridge between Tiger Analytics delivery teams, client stakeholders, and Databricks field engineering teams to drive adoption and expand platform capabilities.
  • Partner directly with clients and engineering teams to turn complex business challenges into production-grade GenAI and Agentic AI solutions, owning the process from initial conversation through live deployment.

About the Company

Tiger Analytics

Delivers Data and AI transformation

Tiger Analytics helps large organizations plan and execute Data and AI–led transformations at scale. It works with clients to translate business needs into data and AI initiatives, using an approach that combines business value mapping, agile operating models, and a platforms-based architecture, backed by partnerships with major hyperscalers. The company designs and delivers end-to-end data and AI solutions—from strategy and data engineering to model development and deployment—so that AI can be applied to tough, real-world problems. Unlike firms that rely mainly on standard playbooks, Tiger Analytics builds custom approaches and accelerators to suit each client’s value chain and operating model. With a global team of 5000+ technologists and consultants, the goal is to enable measurable value and practical outcomes through data and AI programs that work at enterprise scale.

Company size
1,001-5,000
Company stage
Not listed
Total funding
Not listed
Headquarters
San Jose, CA
Founded
2010

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