Job title: Gen AI Architect Client: Care Source # of Positions: 1 Tenure: 2-6 Months (Expected to extend based on the initial 2 month implementation period) Interview Process: Internal & Client
Job Summary:
1) Rapidly assess the customer landscape design and implementation by understanding their processes systems data and pain points to identify and implement high-impact GenAI/agentic opportunities. 2) Define and own the end-to-end solution and technical architecture covering model selection agent design data ingestions integration services guardrails evaluation framework and cost/security posture. 3) Lead the team hands-on through implementation setting engineering and prompt-engineering standards unblocking hard problems and driving an iterative measure-improve-ship cadence. 4) Collaborate with business IT security and engineering stakeholders to manage expectations communicate risks align on goals and keep delivery on track. 5) Own end-to-end delivery and adoption instrument success metrics and establish a post-go-live operating model that sustains measurable productivity gains in production.
Required Skills:
1. Architecting solutioning and implementing scalable multi-agent orchestrated systems leveraging LLMs LangChain/LangGraph ACP and RAG with strong capabilities in agent design patterns workflow orchestration context/memory engineering prompt and tool integration and enterprise-grade observability governance and reliability
2. Python Data Ingestion Data Pipeline Vector DB
3. Azure AI Foundry Azure AI Service (or Similar services)
**Max Vendor Bill Rate: $100/hr****100% Remote**Job title: Gen AI ArchitectClient: Care Source# of Positions: 1Tenure: 2-6 Months (Expected to extend based on the initial 2 month implementation period)Interview Process: Internal & ClientJob Summary:1) Rapidly assess the customer landscape design and...
**Max Vendor Bill Rate: $100/hr** **100% Remote**
Job title: Gen AI Architect Client: Care Source # of Positions: 1 Tenure: 2-6 Months (Expected to extend based on the initial 2 month implementation period) Interview Process: Internal & Client
Job Summary:
1) Rapidly assess the customer landscape design and implementation by understanding their processes systems data and pain points to identify and implement high-impact GenAI/agentic opportunities. 2) Define and own the end-to-end solution and technical architecture covering model selection agent design data ingestions integration services guardrails evaluation framework and cost/security posture. 3) Lead the team hands-on through implementation setting engineering and prompt-engineering standards unblocking hard problems and driving an iterative measure-improve-ship cadence. 4) Collaborate with business IT security and engineering stakeholders to manage expectations communicate risks align on goals and keep delivery on track. 5) Own end-to-end delivery and adoption instrument success metrics and establish a post-go-live operating model that sustains measurable productivity gains in production.
Required Skills:
1. Architecting solutioning and implementing scalable multi-agent orchestrated systems leveraging LLMs LangChain/LangGraph ACP and RAG with strong capabilities in agent design patterns workflow orchestration context/memory engineering prompt and tool integration and enterprise-grade observability governance and reliability
2. Python Data Ingestion Data Pipeline Vector DB
3. Azure AI Foundry Azure AI Service (or Similar services)