Junior Python AI Developer

Experteer Overview In this role you develop and deploy AI agents in production, working with senior engineers and customers to deliver intelligent automation. You will build agent workflows with ADK and Python, connect the platform to customer systems, and continuously improve reliability. You’ll troubleshoot across development and production environments and translate business needs into concrete tasks. This role offers hands-on growth in AI agent tech and exposure to MCP/RAG pipelines in a hybrid Sunnyvale setting. Compensation / Benefits * Design, develop, test, and deploy agent workflows using ADK and Python in production * Create integrations with customer systems, databases, and cloud services via Python and REST APIs * Evaluate agent behavior in real scenarios and iterate to improve reliability * Debug issues across development and production environments * Collaborate with customers and teams to translate requirements into tasks * Build hands-on expertise in AI agents with exposure to MCP and RAG pipelines Tasks * Up to 2 years of software/engineering-related experience * Production-quality Python proficiency (OOP, debugging, testing) * Hands-on ADK experience for building AI agents * REST APIs, JSON, authentication, and third-party integrations * Understanding of prompts, context management, tool usage, model limitations, and evaluation * Strong communication and ownership with good documentation practices * Experience with MCP or RAG pipelines, vector databases, and embeddings * Exposure to cloud platforms (GCP, AWS, or Azure), Docker, or CI/CD pipelines * Customer-facing engineering, consulting, or support experience Key requirements *

Create to MCP and RAG pipelines Tasks * Up to 2 years of software/engineering-related experience * Production-quality Python proficiency (OOP, debugging, testing) * Hands-on ADK experience for building AI agents * REST APIs, JSON, authentication, and third-party integrations * Understanding of prompts, context management, tool usage, model limitations, and evaluation * Strong communication and ownership with good documentation practices * Experience with MCP or RAG pipelines, vector databases, and embeddings * Exposure to cloud platforms (GCP, AWS, or Azure), Docker, or CI/CD pipelines * Customer-facing engineering, consulting, or support experience Key requirements *