AI Engineer

Company Description

Job Description

About the Role

We're looking for an AI Engineer to design, build, and scale the systems that power our AI-driven product. You'll work at the intersection of large language models, multi-agent systems, and production software, turning cutting-edge AI capabilities into reliable, user-facing experiences.

What You'll Do

• Design and implement LLM-powered pipelines, including prompt engineering, context management, and response synthesis
• Build and optimize multi-agent orchestration systems where AI components interact, reason, and produce coherent outputs
• Develop and maintain integrations with foundation model APIs (Anthropic, OpenAI, and others), managing latency, cost, and reliability at scale
• Implement retrieval-augmented generation (RAG) and memory systems for persistent, context-aware behavior
• Partner with the Evaluation/QA Engineer to build frameworks that measure output quality, coherence, and factual grounding
• Collaborate with product and design to translate workflows into robust technical experiences
• Ship production features across the stack, from the model layer to the application

Monitor, debug, and improve system performance, token efficiency, and guardrails

Qualifications

• 3+ years of software engineering experience, with hands-on work building LLM-powered applications
• Strong proficiency in Python and/or TypeScript/JavaScript
• Experience with LLM APIs, prompt engineering, and agentic frameworks (e.g., LangChain, LlamaIndex, or custom orchestration)
• Familiarity with vector databases and RAG architectures (Pinecone, Weaviate, pgvector, etc.)
• Understanding of multi-agent systems, tool use, and function calling
• Experience designing evaluation and testing strategies for non-deterministic AI outputs
• Solid grasp of API design, async processing, and scalable backend architecture
• Comfort working in a fast-moving, ambiguous, early-stage environment

Additional Information

• Experience with real-time streaming (WebSockets, SSE) for conversational interfaces
• Background in fine-tuning, model distillation, or inference optimization
• Familiarity with cloud infrastructure (AWS/GCP/Azure) and CI/CD
• Contributions to open-source AI projects