What are the responsibilities and job description for the Agentic AI Architect position at Smart IT Frame LLC?
Job Title: Agentic AI Architect - LLM orchestration & advanced RAG
Location: Remote (Austin, TX)
Employment Type: Contract/ CTH/ Fulltime
About Smart IT Frame:
At Smart IT Frame, we connect top talent with leading organizations across the USA. With over a decade of staffing excellence, we specialize in IT, healthcare, and professional roles, empowering both clients and candidates to grow together.
Summary:
This role requires a balance of architecture leadership and hands-on engineering, with a strong focus on LLM orchestration, memory management, advanced retrieval (RAG), and enterprise-grade agent workflows.
Experience Level: 15 to 18 years
Must-Have Skills
Recruiters should screen strongly for the following:
1) Agentic AI / LLM Systems
- Proven experience building agentic systems that run-in server environments
- Experience with multi-step orchestration, tool calling, and workflow design
- Hands-on implementation experience — not just conceptual AI knowledge
2) Memory and Context Management
- Experience designing short-term and long-term memory for AI systems
- Understanding of how to manage context across sessions, tasks, and workflows
- Familiarity with state handling, summarization, persistence, and context optimization
3) Advanced Retrieval / RAG
- Strong experience with advanced RAG architectures
- Hands-on work with:
- Vector databases
- Graph databases
- Embeddings and retrieval design
- Experience with hybrid retrieval patterns and building richer context for AI systems
4) Code Intelligence / Technical Analysis
- Experience ingesting source code and documents into AI/retrieval workflows
- Ability to support:
- impact analysis
- dependency mapping
- technical analysis
- code relationship/call graph understanding
- Experience with AST parsing using tools such as Tree-sitter or similar
5) Programming / Engineering Depth
- Strong hands-on experience in:
- Python or Java
- Agentic Platforms, RAG/GraphDB, LLMs
- Caching - near and distributed (Redis ,Apache Ignite etc)
- API Token management optimization techniques is a plus
- Experience with SOLR, Lucene or equivalent is a plus
- AWS Cloud Experience is a plus
- Enough engineering depth to contribute meaningfully to implementation and technical design
6) Frameworks / Platforms
Experience with one or more of the following is important:
- LangGraph
- LangChain
- GitHub Copilot SDK or similar
- CLI-based/server-hosted execution models
- Managed cloud AI platforms such as Bedrock or similar offerings