Forward Deployed Engineer (Generative AI)
About The Position
Tiger Analytics is looking for experienced Forward Deployed Engineer (Generative AI) with Gen AI experience to join our fast-growing advanced analytics consulting firm. Our employees bring deep expertise in Machine Learning, Data Science, and AI. We are the trusted analytics partner for multiple Fortune 500 companies, enabling them to generate business value from data. Our business value and leadership has been recognized by various market research firms, including Forrester and Gartner. We are looking for top-notch talent as we continue to build the best global analytics consulting team in the world. The Forward Deployed Engineer (FDE) drives the on-site deployment, integration, and scaling of our enterprise Generative AI solutions. This role embeds directly within customer engineering teams to operationalize Large Language Models (LLMs) and retrieval systems across multi-cloud environments (AWS, Azure, GCP). You will bridge the gap between AI research and production-grade cloud infrastructure. You will collaborate with cross-functional teams and business partners and will have the opportunity to drive current and future strategy by leveraging your analytical skills as you ensure business value and communicate the results.
Requirements
- Proven experience with Model Garden, Vertex AI Pipelines, and model evaluation.
- Advanced knowledge of SQL for BigQuery, Python for ML engineering, and data preprocessing techniques (scaling, encoding, imputation).
- Hands-on experience with Google Cloud Storage and Vertex AI endpoints.
- Familiarity with stateful real-time processing and the latest innovations in agentic architectures.
Responsibilities
- Develop intelligent agents using Vertex AI Agent Builder to automate complex business workflows.
- Leverage the Agent Developer Kit (ADK) to build and manage multi-agent systems that collaborate to solve end-to-end business challenges.
- Implement tools like MCP (Model Context Protocol) Toolbox to securely connect agents to enterprise databases like BigQuery and Spanner.
- Utilize Vertex AI for model training, tuning, and deployment, ensuring seamless integration with BigQuery for feature engineering.
- Build and optimize streaming data pipelines (e.g., via Dataflow) to execute real-time inference using RunInference API or Vertex AI endpoints.
- Ground AI models in live business context using vector engines within BigQuery or AlloyDB to eliminate "AI amnesia".
- Show up promptly for all internal and client-facing meetings.
- Provide regular, structured status updates to team members and stakeholders regarding project milestones and technical blockers.
- Demonstrate the ability to ask for help when facing technical hurdles and contribute to a collaborative troubleshooting environment.
- Navigate corporate environments to translate high-level business goals into robust technical architectures.
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What This Job Offers
Job Type
Full-time
Career Level
Senior
Education Level
No Education Listed
