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# Senior AI Engineer (LLMs & Agents)

- **Company:** A&A MARKETPLACE LLC
- **Location:** United States (Remote available)
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** LangGraph Framework, Application Programming Interfaces (APIs), Artificial Intelligence, Computer Vision, Cloud Computing, Software Debugging, Python (Programming Language), Machine Learning, Open Source Technology, Performance Tuning, Recommender Systems, OpenAI, Search Technologies, Software Engineering, Pinecone, Qdrant, Retrieval-Augmented Generation, Open-source Models, Large Language Models, Multi-Agent Systems, Fastapi, Build Management, Pgvector, Weaviate, Claude, Virtual Agents, Google Gemini, Model Context Protocol, GPT, Docker, Microservices
- **Published:** November 7, 2026
- **Apply:** https://arc.dev/remote-jobs/j/redirect/px8je7p7ek

## About the Role

* 5+ years of relevant software engineering or machine learning experience.
 * Strong Python programming and backend engineering skills.
 * Hands-on experience building and deploying LLM-powered applications.
 * Experience with AI agent frameworks such as LangGraph, LangChain, or similar tools.
 * Strong understanding of RAG, embeddings, vector search, and retrieval strategies.
 * Experience with LLM tool calling, structured outputs, and orchestration.
 * Knowledge of cloud infrastructure, Docker, APIs, and scalable architectures.
 * Experience evaluating, testing, and monitoring AI systems in production.
 * Strong system design, debugging, and problem-solving skills.

Nice to Have

 * Experience with multi-agent architectures and Model Context Protocol (MCP).
 * Familiarity with fine-tuning, LoRA, and open-source LLM deployment.
 * Experience with vector databases such as Pinecone, Weaviate, Qdrant, or pgvector.
 * Knowledge of recommendation systems, multimodal AI, and computer vision.
 * Experience working in startups, marketplaces, or e-commerce platforms.
 * Experience leading AI engineering projects from prototype to production.

## Description

* Design and build production-grade AI agents powered by Large Language Models (LLMs).
 * Develop multi-agent workflows, tool-calling systems, and autonomous task execution.
 * Build RAG pipelines using embeddings, vector databases, and semantic search.
 * Integrate LLMs such as OpenAI GPT, Claude, Gemini, and open-source models.
 * Design AI-powered marketplace features, including smart search, product recommendations, automated listings, and conversational assistants.
 * Build scalable AI microservices and APIs using Python and FastAPI.
 * Implement evaluation, monitoring, guardrails, and observability for AI systems.
 * Optimize inference performance, latency, token usage, and infrastructure costs.
 * Collaborate directly with founders to define AI strategy and technical architecture.
 * Mentor engineers and establish AI engineering best practices.