Senior AI Engineer (Python)

Key Responsibilities:

• Multi-Agent AI Systems Development: Design, develop, and deploy production-grade multi-agent AI systems capable of autonomous reasoning, task execution, and orchestration across complex workflows.
• Agentic RAG & Multimodal AI Applications: Architect and implement advanced Agentic Retrieval-Augmented Generation (RAG) solutions and multimodal AI applications.
• AI-Powered SaaS Platform Engineering: Build scalable, secure, and high-performance AI-driven SaaS platforms that support enterprise-grade deployments.
• Cloud Architecture & Infrastructure: Design and maintain cloud-native architectures on Google Cloud Platform (GCP).
• Cross-Functional Collaboration: Partner closely with product, engineering, and data teams to translate business objectives into AI-powered capabilities and deliver impactful solutions.
• Technical Leadership & Strategy: Contribute to architectural decision-making, technology roadmaps, and long-term AI strategy.

Expert-level Python development, including software architecture, REST APIs, and production-grade applications.

Experience designing and deploying cloud-native solutions on major cloud platforms (AWS, Azure, or GCP); experience with GCP is a strong plus.

Proven experience building and deploying Generative AI applications, including Agentic RAG, multi-agent systems, conversational AI, and AI-powered SaaS products.

Hands-on experience with at least two AI frameworks such as LangGraph, Google ADK, LlamaIndex, Hugging Face Transformers, or Pydantic AI.

Deep understanding of LLM architectures, including orchestration, tool/function calling, context management, memory systems, and prompt engineering.

Production experience with RAG, semantic search, hybrid search, and vector databases (e.g., Vertex AI Search, Qdrant, Chroma).

Strong knowledge of SQL and modern data platforms, including PostgreSQL, BigQuery, Firestore, and Redis.