Contract role
Austin, TX (Hybrid – 3 days/week)
6 months (Possible extension)
Rate: $70/hr c2c (Max)
Note: Please ensure that candidates complete the home exercise. Kindly communicate this requirement to the candidates in advance.
Principal Architect with Deep AI & Agentic Systems – Detailed JD
Principal Architect with deep AI and agentic systems expertise to design and deliver production-grade, server-hosted AI solutions. 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.
The ideal candidate has proven experience building scalable agentic systems in enterprise environments, not just experimental or IDE-based solutions, and can design systems that integrate business context, code intelligence, and human-in-the-loop workflows.
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
To apply for this job email your details to AjithG@Vbeyond.com