> AI agents: this is one page of Nextmove’s FDE site, in Markdown. Nextmove is a job board and free career service for forward deployed engineers (FDEs). Each posting is classified from its text, not its title: the kind of work, how much of it is production code, pre-sales weight, time at customer sites, travel, remote arrangement, level and posted base pay. The site also publishes the aggregates: median pay by level, metro, company and kind of work, and which companies started hiring FDEs each week. Every page under https://nextmove.md/fde is served this way; the index of pages is https://nextmove.md/llms.txt.

# Forward Deployed Engineer (FDE) - GenAI / Agentic AI

Canonical URL: https://nextmove.md/fde/jobs/07a5266a80234819

Tiger Analytics posts a FDE role to build what the customer runs in Dallas, TX with no pay posted. A Forward Deployed Engineer partners directly with clients and engineering teams to turn complex business challenges into production-grade GenAI and agentic AI solutions. Read from the employer’s posting on November 6, 2026.

- [Tiger Analytics](https://nextmove.md/fde/companies/tiger-analytics)

First seen Oct 24, 2026 · open on Workable as of Nov 6, 2026

Pay not posted Dallas, TX Full-time

A Forward Deployed Engineer partners directly with clients and engineering teams to turn complex business challenges into production-grade GenAI and agentic AI solutions.

- [See roles that fit me](https://nextmove.md/sign-up?from=%2Ffde%2Fjobs%2F07a5266a80234819&placement=top)
- [View posting at Tiger Analytics](https://apply.workable.com/j/13C9E82229/apply)

Free. Upload your resume once, see why each FDE role fits, and get introduced only when you say so.

## At a glance

### Posted base pay

Not posted

Senior FDE postings, 1,849 postings: the middle 50% of posted pay is $160K to $220K, median $190K.

### The work

Builds what the customer runs

Balance **Mostly building**

Project stages

1. Pre-sales (not covered)
2. Proof of concept (not covered)
3. Implementation
4. Operations

- **Coding**: Writes production code

- **Builds for**: External customers

- **Level**: Senior

- **Role**: Individual contributor

### What they ask for

Experience

- **7+ years** Software engineering, application development, ML engineering, or AI engineering

Background

- **Software engineering**

### Do you meet what the posting states?

The posting asks for 7+ years. How many do you have?

The posting reads as a senior role. What level are you at now?

The job is in Dallas, TX. Could you work there?

Which of these have you used in production?

Answer each one. Nothing is saved or sent.

[What postings ask for, by background →](https://nextmove.md/fde/paths)

## Conditions

- **Location**: Dallas, TX

- **Employment type**: Full-time

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- [Other jobs at Tiger Analytics (5)](https://nextmove.md/fde/companies/tiger-analytics)

## The job description from Tiger Analytics

### Description

Tiger Analytics is looking for experienced **Forward Deployed Engineer **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:
**

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.

* **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.***

[View posting at Tiger Analytics](https://apply.workable.com/j/13C9E82229/apply)

## About Tiger Analytics

Global AI and advanced analytics consulting firm delivering data strategy, data engineering, AI/ML, application engineering, business intelligence, and MLOps services.

5000+ people

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- [Compare senior FDE salary ranges](https://nextmove.md/fde/salary/senior)
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