Forward Deployed Engineer (FDE) - GenAI / Agentic AI
Tiger Analytics Inc. Open · verified Oct 22, 2026 At a glance
Mid-level AI Engineering role at Tiger Analytics Inc. Dallas · full-time · no salary stated · we estimate $132,450–$205,151 across the United States.
Tiger Analytics Inc. has not published a salary for this role. The figure below is our estimate, not theirs.
aimlroles summary, based on the employer's posting.
What you'll do
- Work with clients to clarify difficult business problems, then shape them into GenAI and agentic AI solutions
- Build and launch LLM apps, retrieval systems, AI agents and multi-agent workflows, then scale them
- Connect AI systems to company data, APIs, databases and business applications
- Run production cloud deployments and improve systems for speed, scale, reliability, security and cost
- Coordinate with architects, ML engineers, developers and client stakeholders as needs evolve
What you bring
- At least seven years in software, application, ML or AI engineering
- Strong Python skills, plus a solid foundation in APIs, system design, databases and cloud production deployments
- A track record of delivering complete GenAI or agentic AI solutions, including hands-on work with LLMs, RAG and agents
- Practical experience with a major cloud platform and agent orchestration, plus familiarity with LLM evaluation or monitoring
Who this fits
This role suits an experienced engineer who can work directly with clients and move between business conversations and hands-on delivery. You'll need to work independently in ambiguous, fast-moving situations. The position is onsite in Dallas.
From the employer
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.