Forward Deployed Engineer (Generative AI)
SalaryNo pay range posted
LocationNew York, New York, United States
Work modeon-site
Typefull-time
SenioritySenior
DepartmentMLE
Company size5,001–10,000 people
PostedJul 14, 2026 · 3mo ago
Verified live18h ago
At a glanceSummarised by Seekless from the posting.
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
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'
Active Participation: Show up promptly for all internal and client-facing meetings
Transparent Communication: Provide regular, structured status updates to team members and stakeholders regarding project milestones and technical blockers
Proactive Collaboration: Demonstrate the ability to ask for help when facing technical hurdles and contribute to a collaborative troubleshooting environment
Consultative Approach: Navigate corporate environments to translate high-level business goals into robust technical architectures
Vertex AI Mastery: Proven experience with Model Garden, Vertex AI Pipelines, and model evaluation
Data Proficiency: Advanced knowledge of SQL for BigQuery, Python for ML engineering, and data preprocessing techniques (scaling, encoding, imputation)
Cloud Infrastructure: Hands-on experience with Google Cloud Storage and Vertex AI endpoints
Emerging Tech: Familiarity with stateful real-time processing and the latest innovations in agentic architectures
Skills
Vertex AI
BigQuery
Spanner
Dataflow
AlloyDB
SQL
Python
Google Cloud Storage
MCP (Model Context Protocol) Toolbox
RunInference API
About the company
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.
About the role
Role Overview
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
Agentic Design & Implementation
● 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.
AI on Data Strategy
● 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”.
Operational Excellence (Soft Skills)
● Active Participation: Show up promptly for all internal and client-facing meetings.
● Transparent Communication: Provide regular, structured status updates to team
members and stakeholders regarding project milestones and technical blockers.
● Proactive Collaboration: Demonstrate the ability to ask for help when facing
technical hurdles and contribute to a collaborative troubleshooting environment.
● Consultative Approach: Navigate corporate environments to translate high-level
business goals into robust technical architectures.
Technical Qualifications
● Vertex AI Mastery: Proven experience with Model Garden, Vertex AI Pipelines, and
model evaluation.
● Data Proficiency: Advanced knowledge of SQL for BigQuery, Python for ML
engineering, and data preprocessing techniques (scaling, encoding, imputation).
● Cloud Infrastructure: Hands-on experience with Google Cloud Storage and Vertex
AI endpoints.
● Emerging Tech: Familiarity with stateful real-time processing and the latest
innovations in agentic architectures.
Benefits
This position offers an excellent opportunity for significant career development in a fast-growing and challenging entrepreneurial environment with a high degree of individual responsibility.
Tiger Analytics provides equal employment opportunities to applicants and employees without regard to race, color, religion, age, sex, sexual orientation, gender identity/expression, pregnancy, national origin, ancestry, marital status, protected veteran status, disability status, or any other basis as protected by federal, state, or local law.