JB
Technical Lead, Agentic AI
Accepting applicationsJade Business Services (JBS) · Houston, TX
Full-Time Mid_senior AI
Posted
3d ago
Category
Manufacturing
Experience
Mid_senior
Country
United States
JBS builds and operates agentic AI systems for Fortune 500 energy and enterprise clients. We are growing our AI practice and need a Senior AI Engineer who can own the technical execution of complex agentic builds across multiple active accounts.
This is a hands-on engineering role. You will spend the majority of your time building: integrating SDKs, designing and implementing agent workflows, writing and evaluating prompts, connecting data layers, and debugging production behavior. You are expected to work with urgency, operate independently, and move fast inside client environments without waiting to be directed.
Beyond the build, you will read client documentation and technical specs, evaluate solution options, form a point of view, and present it. You will explain complex agent architectures to both technical peers and non-technical stakeholders in plain language. Ideation is part of the role. Clients expect to hear your thinking, not just your output.
What You Will Do
Build and integrate agentic AI solutions using Microsoft Copilot SDK (Copilot Studio, M365 extensibility, declarative agents), Azure AI Foundry, and Azure OpenAI SDK across concurrent client engagements. Design and implement agent workflows using frameworks including Google ADK, LangGraph, LangChain, and CrewAI. Integrate LLMs (Claude, OpenAI, Gemini) with enterprise data sources, APIs, and business systems. Build prompt engineering pipelines and evaluation frameworks. Identify and debug agent reasoning failures, hallucinations, and integration issues in production. Read client architecture documentation, evaluate current-state environments, and produce clear technical assessments. Present solution options and trade-offs to client stakeholders. Work in parallel with other JBS engineers on accounts where multiple workstreams run simultaneously.
Required
7+ years in software engineering or AI/ML engineering roles. Demonstrable hands-on experience building with at least one agentic AI framework (Google ADK, LangGraph, LangChain, CrewAI, or equivalent). Direct experience with Microsoft Copilot SDK or Azure AI Foundry. Working knowledge of LLM tool-use patterns, function calling, and prompt engineering across at least one major LLM provider (Claude, OpenAI, or Gemini). Ability to integrate agents with enterprise systems including APIs, databases, knowledge bases, and identity layers. Able to read technical documentation, form an independent point of view, and articulate it clearly in writing and in conversation. Comfortable presenting to directors and architects without preparation support. Self-directed with a strong sense of urgency. You produce output without a task list and you move fast.
Preferred
Microsoft WorkIQ familiarity. Google ADK experience. GCP ecosystem depth including Vertex AI. Energy, utilities, or other regulated sector domain experience. Prior experience as an embedded consultant inside a client organization.
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This is a hands-on engineering role. You will spend the majority of your time building: integrating SDKs, designing and implementing agent workflows, writing and evaluating prompts, connecting data layers, and debugging production behavior. You are expected to work with urgency, operate independently, and move fast inside client environments without waiting to be directed.
Beyond the build, you will read client documentation and technical specs, evaluate solution options, form a point of view, and present it. You will explain complex agent architectures to both technical peers and non-technical stakeholders in plain language. Ideation is part of the role. Clients expect to hear your thinking, not just your output.
What You Will Do
Build and integrate agentic AI solutions using Microsoft Copilot SDK (Copilot Studio, M365 extensibility, declarative agents), Azure AI Foundry, and Azure OpenAI SDK across concurrent client engagements. Design and implement agent workflows using frameworks including Google ADK, LangGraph, LangChain, and CrewAI. Integrate LLMs (Claude, OpenAI, Gemini) with enterprise data sources, APIs, and business systems. Build prompt engineering pipelines and evaluation frameworks. Identify and debug agent reasoning failures, hallucinations, and integration issues in production. Read client architecture documentation, evaluate current-state environments, and produce clear technical assessments. Present solution options and trade-offs to client stakeholders. Work in parallel with other JBS engineers on accounts where multiple workstreams run simultaneously.
Required
7+ years in software engineering or AI/ML engineering roles. Demonstrable hands-on experience building with at least one agentic AI framework (Google ADK, LangGraph, LangChain, CrewAI, or equivalent). Direct experience with Microsoft Copilot SDK or Azure AI Foundry. Working knowledge of LLM tool-use patterns, function calling, and prompt engineering across at least one major LLM provider (Claude, OpenAI, or Gemini). Ability to integrate agents with enterprise systems including APIs, databases, knowledge bases, and identity layers. Able to read technical documentation, form an independent point of view, and articulate it clearly in writing and in conversation. Comfortable presenting to directors and architects without preparation support. Self-directed with a strong sense of urgency. You produce output without a task list and you move fast.
Preferred
Microsoft WorkIQ familiarity. Google ADK experience. GCP ecosystem depth including Vertex AI. Energy, utilities, or other regulated sector domain experience. Prior experience as an embedded consultant inside a client organization.
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