Fullstack AI Engineer

Role & responsibilities

• 5+ years of experience in software engineering, AI/ML engineering, or full-stack development, with hands-on ownership of building and deploying production-grade applications or platforms.
• Hands-on experience with LLM-based agents, autonomous workflows, or multi-agent orchestration.
• Strong full-stack engineering experience, with deep expertise in Python and familiarity with TypeScript or Node.js.
• Hands-on experience with AI orchestration frameworks such as LangGraph, LlamaIndex Workflows, or similar tools.
• Solid understanding of Retrieval-Augmented Generation (RAG), including hybrid search, re-ranking, and advanced retrieval techniques.
• Experience implementing observability and tracing for AI systems (e.g., LangSmith, LangFuse, Arize Phoenix).
• Production experience with modern ML tooling and frameworks (for example: PyTorch, Transformers, scikit-learn).
• Proven experience taking AI-powered products from prototype to production with strong maintainability and operational quality.
• Proven ability to design and execute evaluation pipelines and testing frameworks to ensure reliability and reduce hallucinations.
• Experience working with APIs/SDKs from major model providers (OpenAI, Anthropic, Gemini) and open-source models.
• Experience deploying and managing services on cloud platforms (AWS, Azure, or GCP) and using containerization (Docker/Kubernetes).
• Familiarity with CI/CD pipelines and DevOps practices.