Who you are

• A hands-on builder with a strong background in Backend or Machine Learning, ready to design, prototype, and deploy high-impact AI solutions.
• An expert in LLMs and Agentic Systems, with proven experience in creating RAG pipelines, prompt engineering, and utilizing multi-agent frameworks (e.g., LangGraph, CrewAI, AutoGen).
• Delivery and quality-oriented, with a curious mindset and a keen focus on continuously improving user experience through iteration and data analysis.
• An effective communicator who is comfortable interacting with engineers, data scientists, and non-technical stakeholders to translate business needs into functional AI conversational flows.

What you will do

• Ships high-impact products in multi-agents systems.
• Design, prototype, and deploy agentic LLM-based bots to assist customers via WhatsApp or other messaging platforms.

• Collaborate with product teams to understand user needs and translate them into conversational flows.
• Implement retrieval-augmented generation (RAG) and tool-use strategies to enhance bot capabilities.
• Continuously test and iterate on prompts, memory systems, and interaction models.

• Monitor bot performance and improve user experience based on feedback and data.
• Develop and manage multi-agent systems, ensuring seamless collaboration between agents across various projects.
• Integrate agents with enterprise platforms like Google Gemini Enterprise, or other multi-agent frameworks like LangGraph to enhance productivity and information retrieval.

• Stay up to date on emerging LLM techniques and propose innovative features.
• Have the right mindset: hands-on, curious, excited about building amazing agentic products that pushes the company towards.

The skills and experience you will bring

• Studies: Bachelor's degree or equivalent experience in quantitative field (Computer Science, Engineering)

• Languages: Python, Node.js, SQL
• Tools: LangChain, multi-agent frameworks (LangGraph, CrewAI, AutoGen), RAG pipelines, LLM APIs (e.g., OpenAI, Claude), Vector DBs (e.g., Pinecone, Weaviate), Docker, FastAPI, Git
• Mandatory experience:
  • Background
    in
    Backend or Machine Learning
  • Practical experience using LLMs (OpenAI, Claude/Anthropic, etc.), prompt engineering, and chaining tools.
  • Strong interest in user experience and how AI can solve real customer pain points.
  • Comfortable talking to data scientists, product managers and non-technical stakeholders.
  • Proven experience in implementing RAG pipelines and a solid understanding of memory modules or experience working with autonomous agents.
  • Familiarity with multi-agent frameworks (LangGraph, AutoGen, CrewAI).