AI Engineer
This AI Engineer role focuses on building scalable, production-grade LLM pipelines and multi-agent systems that deliver coherent, context-aware outputs while balancing cost, latency, and reliability. The position emphasizes hands-on development of RAG systems, API integrations, and quality evaluation frameworks to bridge cutting-edge AI research with real-world user experiences.
Skills required
About this role
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
