Forward Deployed Engineer (Generative AI)

Posted 6 Hours Ago
4 Locations
In-Office or Remote
Mid level
Big Data • Analytics • Business Intelligence • Big Data Analytics
The Role
Embed with client engineering teams to operationalize LLMs and retrieval systems across multi-cloud environments. Build agentic solutions using Vertex AI Agent Builder and ADK, connect agents securely to BigQuery/Spanner via MCP, implement streaming pipelines (Dataflow) for real-time inference, and manage model training, tuning, deployment, and evaluation on Vertex AI. Provide consultative guidance, cross-functional collaboration, and clear stakeholder communication to ensure business value from Generative AI solutions.
Summary Generated by Built In

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.

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.

Skills Required

  • Develop intelligent agents using Vertex AI Agent Builder
  • Experience with Agent Developer Kit (ADK) to build and manage multi-agent systems
  • Familiarity with MCP Toolbox / Model Context Protocol to connect agents to enterprise databases like BigQuery and Spanner
  • Proven experience with Vertex AI for model training, tuning, deployment and model evaluation (Model Garden, Vertex AI Pipelines)
  • Advanced SQL for BigQuery and experience with BigQuery vector engines
  • Python for ML engineering and data preprocessing (scaling, encoding, imputation)
  • Experience building/optimizing streaming data pipelines (Dataflow) and real-time inference using RunInference API or Vertex AI endpoints
  • Hands-on experience with Google Cloud Storage
  • Experience integrating with databases such as AlloyDB and Spanner for retrieval/feature stores
  • Experience deploying and operationalizing solutions across multi-cloud environments (AWS, Azure, GCP)
  • Strong communication, proactive collaboration, and consultative client-facing skills
  • Familiarity with stateful real-time processing and modern agentic architectures

Tiger Analytics Compensation & Benefits Highlights

The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Tiger Analytics and has not been reviewed or approved by Tiger Analytics.

  • Fair & Transparent Compensation Feedback suggests pay is viewed as fair and market-aligned for many roles and geographies. Consistent, on-time pay and competitive packages in key markets reinforce a generally positive baseline.
  • Healthcare Strength Feedback suggests U.S. medical coverage is strong, with administration via a known benefits platform and plan options seen positively. Health insurance is often regarded as a bright spot within the package.
  • Leave & Time Off Breadth Feedback suggests generous PTO, paid sick days and holidays, and flexible PTO alongside remote-work options. These elements indicate broad time-off provisions available on paper.

Tiger Analytics Insights

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The Company
HQ: Santa Clara, CA
5,000 Employees
Year Founded: 2011

What We Do

Tiger Analytics is a global leader in AI and Analytics, helping Fortune 1000 companies solve their toughest challenges. We offer fullstack AI and analytics services & solutions to empower businesses to achieve real outcomes and value at scale. We are on a mission to push the boundaries of what AI and analytics can do to help enterprises navigate uncertainty and move forward decisively. Our purpose is to provide certainty to shape a better tomorrow. Our team of 4000+ technologists and consultants are based in the US, Canada, the UK, India, Singapore, and Australia, working closely with clients across CPG, Retail, Insurance, BFS, Manufacturing, Life Sciences, and Healthcare. We are Great Place to Work-Certified™ and have been recognized by analyst firms such as Forrester, Gartner, Everest, ISG, HFS, and others. Ranked among the ‘Best’ and ‘Fastest Growing’ analytics firms lists by Inc., Financial Times, Economic Times and Analytics India Magazine. In India, our offices are located in Chennai, Hyderabad and Bangalore.

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