Title: GenAI Developer
Location: Westlake Texas (Look for local and Sr. resources) (Hybrid 3 Days/Week)
Duration: 12 Months Contract
USC and GC
Video Interview
Job Description:
Must Have: Clear and recent hands-on experience with Agentic AI and orchestrating agents using Lang Chain Semantic Kernel Auto Gen or Crew AI.
Expert level Python includes asyncio typing Pydantic Fast API and strong experience building Retrieval Augmented Generation systems.
Candidates must have implemented vector databases and integrated LLMs in production environments. If they do not have direct and recent hands-on experience in these areas they will not be a fit.
Interview Process: Not specified. Technical depth will be heavily evaluated.
Candidates must be able to clearly articulate real world implementation experience without relying on theoretical or AI generated responses.
Notes: This requirement has been revised multiple times and the bar is very high.
The hiring panel has indicated that resumes may look strong but candidates have lacked real substance in interviews.
Please be highly selective and ensure candidates have demonstrable hands-on experience with agent orchestration RAG systems vector databases and LLM integrations.
Consider conducting deeper technical screening prior to submission.
Given the niche skill set and rapid evolution of the requirements market rates may exceed prior expectations.
Nice to Have: Production deployment experience of GenAI systems at scale enterprise integration experience and financial services domain exposure.
Title: GenAI Developer Location: Westlake Texas (Look for local and Sr. resources) (Hybrid 3 Days/Week) Duration: 12 Months Contract USC and GC Video Interview Job Description: Must Have: Clear and recent hands-on experience with Agentic AI and orchestrating agents using Lang Chain Se...
Title: GenAI Developer
Location: Westlake Texas (Look for local and Sr. resources) (Hybrid 3 Days/Week)
Duration: 12 Months Contract
USC and GC
Video Interview
Job Description:
Must Have: Clear and recent hands-on experience with Agentic AI and orchestrating agents using Lang Chain Semantic Kernel Auto Gen or Crew AI.
Expert level Python includes asyncio typing Pydantic Fast API and strong experience building Retrieval Augmented Generation systems.
Candidates must have implemented vector databases and integrated LLMs in production environments. If they do not have direct and recent hands-on experience in these areas they will not be a fit.
Interview Process: Not specified. Technical depth will be heavily evaluated.
Candidates must be able to clearly articulate real world implementation experience without relying on theoretical or AI generated responses.
Notes: This requirement has been revised multiple times and the bar is very high.
The hiring panel has indicated that resumes may look strong but candidates have lacked real substance in interviews.
Please be highly selective and ensure candidates have demonstrable hands-on experience with agent orchestration RAG systems vector databases and LLM integrations.
Consider conducting deeper technical screening prior to submission.
Given the niche skill set and rapid evolution of the requirements market rates may exceed prior expectations.
Nice to Have: Production deployment experience of GenAI systems at scale enterprise integration experience and financial services domain exposure.
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