> Markdown version of [/jobs/ext/4391993-sr-gen-ai-engineer](https://www.wearedevelopers.com/jobs/ext/4391993-sr-gen-ai-engineer). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md).

---

# SR GEN AI Engineer

- **Company:** Quantum Technologies
- **Location:** Dallas, TX, United States
- **Experience:** Expert
- **Salary:** $180,960.0
- **Contract:** Contract
- **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Amazon Web Services, Databases, Information Engineering, Performance Tuning, Search Technologies, Systems Integration, Enterprise Software Applications, Retrieval-Augmented Generation, Large Language Models, Multi-Agent Systems, Generative AI, Backend, Agentic-AI, Low Latency, Data Management, Virtual Agents, Model Context Protocol, Data Pipelines
- **Published:** October 31, 2026
- **Apply:** https://www.dice.com/job-detail/425d70e3-7074-4918-a1cd-f5b8c84aee6a

## About the Role

* Proven experience delivering at least one end-to-end LLM, RAG, or Agentic AI project.
 * Strong architectural and hands-on experience with Generative AI on AWS.
 * Hands-on knowledge of LLMs, RAG, embeddings, vector search, and agentic workflows.
 * Experience integrating AI agents with APIs, databases, backend services, and enterprise systems.
 * Understanding of MCP (Model Context Protocol) and agent-to-tool/service integration.
 * Experience with Lakehouse and Medallion Architecture and data pipeline optimization.
 * Strong understanding of AI testing, observability, security, scalability, latency, and production performance.
 * Ability to articulate end-to-end architecture, technology choices, integration patterns, and design trade-offs.

Preferred

 * Experience with AWS-based GenAI and data platforms.
 * Experience building enterprise-scale AI agents or multi-agent solutions.
 * Exposure to modern vector databases, Lakehouse technologies, and AI orchestration frameworks.
 * Strong technical leadership and stakeholder communication skills.

## Description

Seeking a Store AI Agent Lead to architect, build, and scale AI-powered agents supporting store operations. The role requires strong hands-on experience with Agentic AI, LLMs, RAG, vector search, AWS, and enterprise system integration, along with the ability to take solutions from architecture through production., * Lead the end-to-end architecture and implementation of Store AI Agents.

 * Design agentic workflows integrating LLMs with APIs, databases, backend services, enterprise applications, and MCP servers.
 * Build and optimize RAG solutions, including embeddings, retrieval, vector search, grounding, and context management.
 * Define the process for onboarding and integrating new AI agents, including testing, deployment, monitoring, and production readiness.
 * Establish clear architecture between LLM reasoning/generation and deterministic backend services.
 * Leverage Lakehouse/Medallion architecture (Bronze, Silver, Gold) to support AI and data use cases.
 * Define scalable approaches for AI/RAG testing, validation, observability, and performance optimization.
 * Address production challenges including latency, context limitations, retrieval quality, scalability, and reliability.
 * Provide technical leadership across AI/ML, data engineering, cloud, application, and business teams.