Agentic AI Developer

What You Will Work On

• Develop and integrate new domain-specific AI agents into an existing multi-agent orchestration system built on LangGraph and LangChain
• Design and implement SQL generation agents that translate natural language questions into precise Snowflake SQL, enforcing business rules, RBAC, and fiscal period logic
• Build and consume MCP (Model Context Protocol) server integrations for secure, structured data access across enterprise data sources
• Work with PromptQL and RAG/PageIndex patterns to improve query accuracy, context retrieval, and domain-specific grounding
• Develop FastAPI endpoints and async workflows to support real-time query processing, background job execution, and frontend integration
• Create intelligent data visualization pipelines that automatically select and generate the right chart type (heatmaps, bar charts, KPIs) based on query results and user intent
• Write domain context configurations (JSON schemas) that define column mappings, business rules, valid values, and metric definitions for each data domain
• Contribute to a plugin-based domain registry architecture that allows new agents to be added without modifying core orchestration code

Mandatory skills

• Python - Expert-level proficiency; ability to write production-quality async code, work with complex class hierarchies, and debug multi-layer systems
• Snowflake - Strong experience writing and optimizing analytical SQL; understanding of RBAC patterns, fiscal period logic, and aggregation queries
• LangGraph / LangChain - Hands-on experience building stateful, multi-step AI agent workflows with tool calling, checkpointing, and conditional routing
• RAG / PageIndex - Practical experience implementing retrieval-augmented generation pipelines for context-aware AI applications
• MCP (Model Context Protocol) - Practical experience with MCP client/server patterns for structured tool-to-data communication
• Snowflake Cortex - Experience with Snowflake Cortex AI functions (COMPLETE, EXTRACT_ANSWER, SUMMARIZE, SENTIMENT) and building AI/ML workflows natively within Snowflake
• PromptQL - Experience with structured prompt engineering and query language patterns for grounding LLM outputs in enterprise data