Key skills
CloudGoogle Cloud PlatformPythonAILLMRAGLangChainLlamaIndexAgenticLangGraphPineconeWeaviateMilvusGCPGoogle Cloud
About this role
Role Overview
- Build and maintain sophisticated, multi-step AI agents that can reason, plan, and execute tasks using tools and internal APIs
- Transition AI concepts from POC to production-ready software by writing clean, maintainable, and tested Python code
- Collaborate closely with Backend and Software Engineering teams to expose AI capabilities via robust and secure APIs
- Implement and optimize Retrieval-Augmented Generation (RAG) pipelines using vector databases and efficient retrieval strategies
- Design systems with monitoring in mind, tracking the performance, cost, and accuracy of the agents you deploy
- Take end-to-end ownership of agent logic, ensuring AI behavior aligns with business goals and technical constraints
Requirements
- 3+ years of experience in Software Engineering or Data Science, with at least 1 year of strong focus on LLMs and agentic workflows
- University degree in Computer Science, AI, Data Science, or comparable industry experience
- Strong, production-grade Python skills with experience structuring full applications rather than just scripts or notebooks
- Hands-on experience with modern LLM frameworks such as LangChain, LangGraph, LlamaIndex, or custom equivalents
- Deep understanding of agentic patterns, state management, memory persistence, and orchestration of multi-step workflows
- Experience with vector databases (e.g., Pinecone, Weaviate, Milvus) and retrieval systems
- Experience deploying to cloud environments (preferably GCP) and integrating LLMs with external APIs and tools
- Ability to reason about engineering fundamentals including system latency, token costs, rate limits, and failure recovery
- A production-oriented mindset that prioritizes reliability, ownership, and solving actual business problems
- Excellent knowledge of written and spoken English
Tech Stack
- Cloud
- Google Cloud Platform
- Python
Benefits
- Experience-based compensation package
- Remote or hybrid work model
- 30 free days
- Educational learning opportunities to support each employee's professional growth journey
- Sports activities, team building, and informal gatherings
- Free drinks, fruit, and ice cream