Key Responsibilities :

- Build and support AI agents and agent workflows using frameworks such as LangGraph or custom architectures

- Implement structured workflows where LLMs interact with backend logic

- Integrate LLM APIs with tool calling, structured outputs, guardrails, fallback handling, retry and validation mechanisms

- Develop backend infrastructure including API layers, reusable modules, middleware, agent orchestration workflows, and persistence/memory layers

- Deploy services on Google Cloud Platform using tools like Cloud Run, Vertex AI, and BigQuery

- Integrate systems with BigQuery for data retrieval, storage, prompts, and logs

- Support monitoring, logging, workflow tracking, and reliability of AI services

Requirements :

- 2 years of backend development experience

- Strong experience with Python backend development

- Experience working with cloud platforms (preferably GCP)

- Understanding of REST APIs, service integration, and authentication

- Exposure to LLMs, AI agents, or AI-powered applications

- Experience with databases or data warehouses (BigQuery preferred)

- Ability to write clean, modular, and maintainable code

Good to Have :

- Experience with LangChain, LangGraph, or similar AI orchestration frameworks

- Familiarity with workflow-based backend systems and structured data pipelines

- Experience deploying services on Cloud Run or containerized environments

- Interest in AI infrastructure and intelligent systems