Forward Deployed Engineer (Generative AI)

Tiger Analytics Inc.

  • Dallas, TX
  • 30+ days ago
  • Remote
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    Skills

    • Amazon Web Services (AWS)unmatched
    • Analysis Skillsunmatched
    • Application Programming Interface (API)unmatched
    • Artificial Intelligence (AI)unmatched
    • Artificial Intelligence (AI) Agentsunmatched
    • Channel Strategiesunmatched
    • Cloud Computingunmatched
    • Consultingunmatched
    • Cross-Functionalunmatched
    • Customer Relationsunmatched
    • Data Managementunmatched
    • Data Scienceunmatched
    • Emerging Technologyunmatched
    • Entrepreneurshipunmatched
    • Fortune 500 Customersunmatched
    • GCP (Good Clinical Practices)unmatched
    • Identify Issuesunmatched
    • Leadershipunmatched
    • MCP - Microsoft Certified Professionalunmatched
    • Machine Learningunmatched
    • Market Researchunmatched
    • Microsoft Windows Azureunmatched
    • Modeling Languagesunmatched
    • Python Programming/Scripting Languageunmatched
    • SQL (Structured Query Language)unmatched
    • Software Agentsunmatched
    • Team Playerunmatched
    • Technical Supportunmatched

    Description

    Tiger Analytics is looking for experienced Forward 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

    The Forward 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.

    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.

    Numbers & Facts

    LocationDallas, TX (
    Remote
    )

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