Senior AI Agent Engineer

We are developing Keewano AI Analytics Agent — a next-generation agentic analytics platform built on top of KeewanoDB, the first real-time database optimized for AI agents at scale.

We are looking for a Senior AI Agent Engineer to build data-intensive, multi-agent systems that reason over real-time data and power agentic analytics workflows. This role sits at the intersection of LLMs, data systems, and distributed infrastructure, with a strong focus on the GCP / Gemini ecosystem.

• Design and build multi-agent systems for real-time data analysis and decision-making
• Develop agentic analytics workflows over time-series and unstructured data
• Build and deploy LLM-powered agents using Google ADK (Agent Development Kit) and Gemini
• Design and iterate on prompting strategies, tool usage, and agent behavior
• Integrate agents deeply with KeewanoDB for real-time querying, reasoning, and action
• Build backend services and orchestration layers in Python
• Combine structured, unstructured, and streaming data into coherent agent pipelines
• Evaluate and improve agent reliability, latency, and correctness in production
• Collaborate with platform and database teams to define agent–data interaction patterns

• 4–7+ years of experience in software engineering, with focus on backend or AI systems
• Strong proficiency in Python
• Hands-on experience building with LLMs (Gemini, OpenAI, etc.) in production environments
• Experience with Google ADK or similar agent frameworks
• Experience with prompt engineering, tool calling, and agent design patterns
• Familiarity with multi-agent architectures and orchestration approaches
• Experience working with data systems (analytics, pipelines, or large-scale datasets)
• Strong understanding of APIs, system integration, and distributed systems fundamentals

• Experience with the GCP AI stack (Gemini, Vertex AI, BigQuery, Pub/Sub, etc.)
• Background in analytics systems or data-intensive applications
• Experience building custom agent orchestration frameworks
• Experience designing evaluation frameworks for LLM / agent performance
• Familiarity with streaming systems and real-time architectures

• Build next-generation AI agent systems that operate on real-time data
• Work on agentic analytics — where AI systems reason, decide, and act on live data
• Operate at the intersection of LLMs, data infrastructure, and real-time systems
• Shape how AI agents interact with data at scale
• Own critical parts of the system from early stages