Tiger Analytics

Forward Deployed Engineer (FDE) - GenAI / Agentic AI

Tiger Analytics • $125K — $150K *
Dallas, TX 75217In-Person
Information Technology
5 - 7 years of experience
Today
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Job Overview by Ladders

Qualifications

  • 7+ years in software engineering, application development, ML engineering, or AI engineering.
  • Strong Python programming skills.
  • Solid grasp of APIs, system design, databases, and cloud-native applications.
  • Proven experience in building and deploying GenAI/Agentic AI solutions.
  • Hands-on experience with LLMs, including OpenAI, Anthropic Claude, and Google Gemini.
  • Familiarity with agent orchestration and multi-agent systems.
  • Experience with major hyperscalers (AWS, Azure, GCP) including specific technologies in each stack.

Responsibilities

  • Partner with clients to identify and translate complex business challenges into AI solutions.
  • Design and deploy applications using LLMs and AI agents.
  • Integrate AI solutions with existing enterprise data and business applications.
  • Operate and scale AI solutions in production cloud environments.
  • Troubleshoot production systems for performance and reliability.
  • Collaborate with various stakeholders in dynamic settings.

Benefits

  • Significant career development opportunities.
  • Work in a fast-growing and entrepreneurial environment.
  • High degree of individual responsibility.
Full Job Description
Role Overview:
We're looking for a Forward Deployed Engineer who thrives at the intersection of client problem-solving and hands-on AI engineering. You'll partner directly with clients and engineering teams to turn complex business challenges into production-grade GenAI and Agentic AI solutions - owning the journey from first conversation to live deployment.

Requirements
  • Partner directly with clients to understand complex business problems and translate them into GenAI and Agentic AI solutions.
  • Design, build, deploy, and scale LLM applications, RAG systems, AI agents, and multi-agent workflows.
  • Integrate AI solutions with enterprise data, APIs, databases, and business applications.
  • Deploy, operate, and scale solutions in production cloud environments.
  • Troubleshoot and optimize production systems for performance, scalability, reliability, security, and cost.
  • Collaborate closely with architects, ML engineers, developers, and client stakeholders in fast-moving, ambiguous environments.


Qualifications:

Engineering Foundation
  • 7+ years in software engineering, application development, ML engineering, or AI engineering.
  • Strong Python programming skills.
  • Solid grasp of APIs, system design, databases, cloud-native applications, and production deployments.
  • JavaScript/TypeScript experience is a plus.


GenAI / Agentic AI Expertise
  • Proven experience building and deploying end-to-end GenAI and/or Agentic AI solutions.
  • Hands-on experience with LLMs - OpenAI, Anthropic Claude, Google Gemini, and open-source models.
  • Hands-on experience with RAG, vector databases, embeddings, tool/function calling, and AI agents.
  • Experience with agent orchestration, multi-agent systems, or agentic workflows.
  • Familiarity with frameworks such as LangGraph, LangChain, LlamaIndex, Google ADK, or similar.
  • Working knowledge of MCP, A2A, or similar agent integration protocols.


Cloud & Production
  • Hands-on experience with at least one major hyperscaler - AWS, Azure, or GCP - including targeted expertise in:
  • AWS Stack: Designing workflows via Amazon Bedrock (Claude, Llama), deploying scalable RAG using OpenSearch Serverless (Vector Engine), and configuring Bedrock Guardrails for client VPCs.
  • Azure Stack: Deploying enterprise LLMs via Azure OpenAI Service (PTU optimization), building hybrid RAG systems with Azure AI Search, and orchestrating flows using Azure AI Foundry and Semantic Kernel.
  • GCP Stack: Scaling applications within Vertex AI, managing production pipelines, structuring enterprise RAG with Vertex AI Vector Search + BigQuery, and building agentic flows with Gemini APIs.
  • Exposure to LLM evaluation, observability, monitoring, guardrails, or LLMOps.


The FDE Mindset
  • Strong customer-facing communication and sharp problem-solving instincts.
  • Comfortable operating independently, navigating ambiguity, and moving fast from problem  solution  production.
  • Equally at home with business and technical stakeholders.


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.

About Tiger Analytics

Tiger Analytics is a consulting firm that provides data analytics consulting services to businesses. The company specializes in data science, machine learning, and artificial intelligence. Tiger Analytics helps businesses to leverage data to make better decisions, improve operations, and drive growth. The company has worked with clients in a variety of industries, including healthcare, retail, finance, and technology.
Learn more about Tiger Analytics
Size
500 employees
Industry
Information Technology
Net Income
$1 million
Founded
2011
5 Year Trend
+50%
Revenue
$10 million
* Ladders Estimates

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