A SaaS? control plane for designing, orchestrating, and evaluating LLM?-powered agent workflows across enterprise tools.
Added Jun 10, 2026
Medium opportunity (64%)
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Companies are hiring for agent frameworks, prompt engineering, tool calling, RAG? pipelines, and orchestration expertise because building reliable agentic AI systems still requires scarce specialist talent. Teams struggle to translate business workflows into production-ready AI automations with measurable quality, safe tool use, and repeatable evaluation.
AgentFlow provides a visual and code-friendly workspace to map business workflows into agent graphs, connect tools and RAG? pipelines, manage prompts, and run evaluations before deployment. It gives engineering and transformation teams reusable orchestration templates, tool-calling controls, trace logs, and regression tests for LLM?-based applications.
Job postings across Apple, LangChain, ByteDance, Hippocratic AI, Disco, and others show that agent orchestration has moved from experimentation into infrastructure hiring. Enterprises now need repeatable platforms rather than bespoke agent builds for every workflow.
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You will own outcomes end to end. That means the agent, the evaluation harness that proves it works, and the surface our customers actually touch. Design and implement agent workflows using LangGraph/LangChain, with a strong focus on orchestration, observability and debugging.
Architect and implement end-to-end AI pipelines, including data ingestion, processing, model integration, and agent orchestration. Build and optimize agentic workflows using LLMs, RAG architectures, APIs, and orchestration frameworks.
You can translate the industry patterns into the emerging AI Agent observability domain, including agentic workflows, LLM spans, experiments, evaluations, and prompt templates You build deep context across teams and translate it into reusable, scalable solutions
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