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Role: Software Developer 2 - C2C - Austin, TX (Hybrid) - In person Interview
Experience in AI/ML engineering or advanced data science
Proven track record of building and deploying production-grade autonomous agents.
Strong experience in context engineering
Deep experience with LangChain, LangGraph, CrewAI, or AutoGPT.
Experience implementing RAG architectures using vector databases
Proficiency in Python and AI/ML libraries (OpenAI, Hugging Face, Azure AI)
Experience integrating LLMs via APIs Knowledge of AI governance, model lifecycle management, and evaluation
Experience implementing and extending the Model Context Protocol (MCP) to provide LLMs with secure, standardized access to local and remote data sources Experience implementing AI guardrails, content filtering, and safety controls
Understanding of data privacy and handling of sensitive data (PII/PHI)
Experience building multi-agent or autonomous agentic workflows
Experience optimizing LLM cost, token usage, and performance
Familiarity with enterprise AI deployment patterns and scalability considerations
Role: Software Developer 2 - C2C - Austin, TX (Hybrid) - In person Interview
Experience in AI/ML engineering or advanced data science
Proven track record of building and deploying production-grade autonomous agents.
Strong experience in context engineering
Deep experience with LangChain, LangGraph, CrewAI, or AutoGPT.
Experience implementing RAG architectures using vector databases
Proficiency in Python and AI/ML libraries (OpenAI, Hugging Face, Azure AI)
Experience integrating LLMs via APIs Knowledge of AI governance, model lifecycle management, and evaluation
Experience implementing and extending the Model Context Protocol (MCP) to provide LLMs with secure, standardized access to local and remote data sources Experience implementing AI guardrails, content filtering, and safety controls
Understanding of data privacy and handling of sensitive data (PII/PHI)
Experience building multi-agent or autonomous agentic workflows
Experience optimizing LLM cost, token usage, and performance
Familiarity with enterprise AI deployment patterns and scalability considerations