Forward Deployed Engineer, Generative AI

Role Overview

• Drive the on-site deployment, integration, and scaling of enterprise Generative AI solutions.
• Embed directly within customer engineering teams to operationalize Large Language Models (LLMs) and retrieval systems across multi-cloud environments (AWS, Azure, GCP).
• Bridge the gap between AI research and production-grade cloud infrastructure.
• Collaborate with cross-functional teams and business partners to leverage analytical skills and ensure business value.

Requirements

• 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".
• 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.

Tech Stack

• AWS
• Azure
• BigQuery
• Cloud
• Google Cloud Platform
• Python
• SQL

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.