AI Agent Engineer
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| 10. | Marketing Productivity Engineer (Sigma Computing) San Francisco, United States+2 | $130,000 – $165,000/yr | on-site | full-time | senior | performance marketing, growth engineering, marketing operations | 4w ago |
About Us
We are an AI-powered local discovery platform that helps people explore cities and find great places effortlessly. By combining conversational AI, interactive maps, and community-driven content, we enable users to discover restaurants, attractions, and unique local experiences through natural, intuitive interactions. We are building the next generation of AI-powered discovery, reimagining how people explore the world around them.
About the Role
We are looking for an AI Agent Engineer to design, build, and scale production-grade AI Agent systems that power conversational search, personalized recommendations, and end-to-end local discovery experiences. You will own the full lifecycle of Agent architecture, reasoning logic, tool orchestration, and RAG pipelines, turning cutting-edge LLM capabilities into reliable, user-facing systems that directly improve product experience and business metrics.
Responsibilities
- Design and implement production AI Agent / Multi-Agent systems for conversational search, recommendation, and local discovery.
- Build and optimize Agent core modules: planning, memory, tool use, function calling, reflection, and workflow orchestration.
- Develop and scale RAG + multimodal retrieval pipelines across text, image, video, POI, and structured data.
- Integrate, fine-tune, and deploy LLMs and vision-language models for real-time Agent inference.
- Improve query understanding, intent recognition, and response relevance for consumer-facing conversational AI.
- Run A/B tests, analyze performance, and drive measurable improvements in user experience, latency, and quality KPIs.
- Build scalable, low-latency Agent systems that support millions of user interactions.
Requirements
- Bachelor’s degree or above in Computer Science, Artificial Intelligence, or related fields, with solid engineering fundamentals.
- Hands-on experience building and shipping LLM Agent / RAG systems in production.
- Deep understanding of Agent frameworks: LangChain / LlamaIndex / LangGraph or similar.
- Experience with retrieval, embeddings, vector databases, and multimodal models.
- Familiarity with LLM optimization: SFT, LoRA, DPO, inference acceleration is a strong plus.
- Proficiency in Python; experience with Go/C++ is a plus.
- Experience building scalable ML/AI systems in search, recommendation, NLP, or consumer AI products.
- Fast learner, self-driven, and comfortable in a fast-paced startup environment.