Intone
From Intone's careers page
Status: listed on the employer's own careers page when we last checked (daily). Confirm on their site before applying.
We are seeking an Agentic AI Engineer with hands-on experience building and deploying production-grade AI agents in enterprise environments.
This is a 6-month contract position based in Plano, Texas, working onsite. We are seeking an Agentic AI Engineer with hands-on experience building and deploying production-grade AI agents in enterprise environments.
Design, build, and deploy AI agents into production environments serving real users.
Develop and orchestrate multi-agent workflows, tool integrations, and autonomous decision-making frameworks.
Develop, test, and optimize AI-driven applications that leverage large language models, agent frameworks, and retrieval capabilities.
Design and implement RAG (Retrieval-Augmented Generation) architectures using vector databases.
Implement agentic workflow patterns including tool calling, ReAct frameworks, and Human-in-the-Loop workflows.
Troubleshoot, monitor, and support AI-enabled applications in production environments.
Optimize latency, throughput, and inference costs for LLM applications.
Implement guardrails and responsible AI practices to reduce hallucinations and unsafe outputs.
Collaborate on enterprise architecture, scalability, reliability, and observability requirements.
Required
Strong proficiency in both Python and Java, with hands-on experience developing and supporting production-grade applications.
Demonstrated experience building, deploying, and maintaining Agentic AI solutions in enterprise environments.
Experience designing and orchestrating multi-agent workflows, tool integrations, and autonomous decision-making frameworks.
Hands-on experience with LangChain and/or LangGraph.
Experience with tool calling, ReAct frameworks, and Human-in-the-Loop (HITL) workflows.
Experience designing and implementing RAG architectures and working with vector databases such as Pinecone, Milvus, or Weaviate.
Experience with vLLM and LLM deployment/inference frameworks.
Strong understanding of API development, microservices architectures, and integration patterns within modern software ecosystems.
Ability to design, build, and deploy AI agents to production serving real users, with demonstrable business outcomes and adoption metrics.
Understanding of scalability, reliability, observability, and enterprise architecture.
Familiarity with responsible AI practices, model governance, security considerations, and enterprise development standards.
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