LLM Engineer (AI Agents) - Wisy

LLM Engineer, AI Agents

📍 Remote | 🕐 Full-time | đŸ€–Â Applied AI / LLMs / Agents / Retail Tech

Wisy is building intelligent AI agents that transform fragmented retail data into smart actions. We’re looking for an LLM Engineer to lead the design and optimization of domain-specific language models and agentic workflows that power real-time insights.

đŸ’Œ What You’ll Do:

  • Design and implement LLM-based agents tailored for retail and CPG applications
  • Fine-tune large language models (open-source or commercial) on domain-specific data
  • Build and optimize prompt templates and instruction pipelines
  • Evaluate models using internal benchmarks and real-world performance
  • Collaborate with Product to scope model capabilities based on user needs
  • Develop RAG systems and integrate vector stores for contextual reasoning
  • Deploy LLMs in production environments with robust monitoring
  • Ensure compliance with data privacy, latency, and compute constraints
  • Design fallback, reinforcement, and human-in-the-loop strategies
  • Contribute to agentic architecture and internal tooling
  • Collaborate with engineering on scalability and integrations
  • Maintain documentation and reproducibility of experiments
  • Stay up to date with advancements in LLMs and agent frameworks
  • Mentor junior team members and help establish best practices
  • Conduct applied research and prototype new model features

đŸ§© What You’ll Bring:

  • 3+ years of experience working with LLMs, NLP, or ML pipelines
  • Hands-on experience with frameworks like LangChain, Hugging Face, OpenAI, Pinecone, etc.
  • Deep understanding of prompt engineering, fine-tuning, and embeddings
  • Experience deploying models in production environments
  • Strong Python and ML development skills
  • Passion for AI agents and solving real-world business problems

🌎 Why Join Us?

  • Direct impact on the AI backbone of a fast-growing startup
  • Work with a mission-driven team solving complex problems
  • Remote-friendly, flexible environment
  • Competitive comp, stock options, and learning opportunities