| Minimum Requirements: Candidates that do not meet or exceed the minimum stated requirements (skills/experience) will be displayed to customers but may not be chosen for this opportunity. | ||
| Years | Required/Preferred | Experience |
| 4 | Required | experience in AI/ML engineering or advanced data science |
| 4 | Required | Proven track record of building and deploying production-grade autonomous agents. |
| 4 | Required | Strong experience in context engineering |
| 4 | Required | Deep experience with LangChain, LangGraph, CrewAI, or AutoGPT. |
| 4 | Required | Experience implementing RAG architectures using vector databases |
| 4 | Required | Proficiency in Python and AI/ML libraries (OpenAI, Hugging Face, Azure AI) |
| 4 | Required | Experience integrating LLMs via APIs Knowledge of AI governance, model lifecycle management, and evaluation |
| 4 | Required | 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 |
| 4 | Required | Understanding of data privacy and handling of sensitive data (PII/PHI) |
| 2 | Preferred | Experience building multi-agent or autonomous agentic workflows |
| 2 | Preferred | Experience optimizing LLM cost, token usage, and performance |
| 2 | Preferred | Familiarity with enterprise AI deployment patterns and scalability considerations |