Forward Deployed Engineer (Generative AI)

Tiger Analytics, LLC; Canada; On-site; CAD 150,000 - 210,000; Full time

Job summary

Tiger Analytics is seeking a Forward Deployment Engineer to drive on-site deployment, integration, and scaling of enterprise Generative AI solutions within customer environments.

You will bridge AI research and production-grade cloud infrastructure across AWS, Azure, and GCP, collaborating with cross-functional teams to ensure business value and reliable operation of AI systems.

Qualifications

• Proven experience with Vertex AI, agents, and multi-agent systems.
• Strong SQL (BigQuery) and Python for ML engineering.
• Hands-on experience with GCP services: BigQuery, Spanner, Dataflow.
• Familiarity with real-time data pipelines and model deployment.
• Ability to translate business needs into scalable AI architectures.

Responsibilities

• Lead on-site deployment and integration of enterprise Gen AI solutions.
• Collaborate with cross-functional teams to operationalize LLMs and retrieval systems.
• Design and implement agent-based architectures using Vertex AI tools.
• Ensure robust data pipelines and real-time inference across multi-cloud environments.

Skills

Vertex AI Mastery

SQL (BigQuery)

Python ML

Data preprocessing

Real-time streaming

Tools

Vertex AI Agent Builder

ADK

MCP Toolbox

BigQuery

Spanner

Dataflow

RunInference API

Job description

Tiger Analytics is looking for experiencedForward Deployment 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.

Role Overview

TheForward Deployment 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.

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.

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.