Senior AI Engineer (Agentic AI / Automation)

kcg staffing•Denver, CO

3d•Onsite

About The Position

Our Direct Client is on a mission to digitally transform the supply chain — empowering businesses to become more efficient, sustainable, and intelligent through cutting-edge AI. Our platform enables automation and decision-making at scale, driving real-world impact across logistics, transportation, and commerce. We’re not just optimizing — we’re reimagining how humans and machines collaborate. We’re looking for a Senior AI Engineer with a true Agentic AI background — someone who’s built agents in production, not just read about them. If you’re passionate about creating intelligent systems that can reason, orchestrate, and reduce “human things,” this role is for you. In this high-impact position, you’ll design and deploy AI agents that can build, manage, and optimize other agents — automating workflows and scaling human efficiency. You’ll collaborate with an incredible engineering team to push the boundaries of how AI can transform real-world operations. This is a hands-on engineering role — no time for training wheels. You’ll hit the ground running, designing, coding, and deploying intelligent automation that makes an immediate impact.

Requirements

5+ years of experience as a software or AI engineer in fast-paced environments.
Hands-on experience building and deploying AI agents in production environments.
Deep proficiency in Python (must be able to write production-quality code).
Strong understanding of Agentic AI , RAG , LangGraph , ClaudeAI , Autogen , or related frameworks.
Solid grasp of AI orchestration — how agents interact, collaborate, and execute workflows.
Experience building on MCP Servers or similar multi-agent coordination platforms.
Strong architectural understanding of modern AI systems.
A self-starter mindset — you thrive in autonomy, deliver results quickly, and adapt fast.

Nice To Haves

(Bonus) Experience in supply chain, logistics, or workflow automation domains.

Responsibilities

Build, deploy, and iterate on Agentic AI systems — agents that can collaborate, learn, and automate workflows.
Orchestrate existing agents to build new agents (yes, agents that build agents).
Integrate and optimize workflows using ClaudeAI , LangGraph , Autogen , and similar frameworks.
Work extensively with Python to develop production-grade AI applications.
Implement Retrieval-Augmented Generation (RAG) pipelines for dynamic reasoning and contextual responses.
Develop on top of platforms like MCP Servers and other orchestration frameworks.
Collaborate cross-functionally with Product and Operations teams to automate key business processes.
Design systems that “reduce human things” — freeing up people to focus on high-value work.