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Senior AI Engineers

Empower ProfessionalsChicago, IL🇺🇸United StatesPosted Sep 17, 2026

Why This Role Stands Out

This role offers a unique opportunity to shape the future of enterprise AI engineering, leading hands-on development of innovative solutions that deliver tangible business impact. You'll thrive here if you're a seasoned AI engineer eager to mentor teams, build impactful frameworks, and drive client success within a highly visible, collaborative environment. Apply now to be at the forefront of AI transformation and elevate your career.

Quick Overview

Seniority
Mid Senior
Work mode
On Site
Location
Chicago, IL, United States
Posted
Yesterday
Python

Job Description

Role: Senior AI Engineers (CGEMJP00356724)

Duration: 12 Months

Work site: Chicago, IL (Fully Onsite)

Job Description/Role:

Client is building the next generation of enterprise AI engineering capabilities and is seeking experienced AI Tech Leads and Senior AI Engineers who thrive at the intersection of innovation, software engineering, and client delivery. This is a highly visible, hands-on role responsible for helping enterprise clients transform how software is designed, developed, tested, deployed, and supported using Artificial Intelligence. The successful candidate will work directly with client executives, architects, and engineering teams to build production-ready AI solutions that deliver measurable business outcomes. Rather than simply advising on AI strategy, this individual will lead by building, mentoring, and executing alongside delivery teams while establishing Client as a trusted AI transformation partner.

Objectives

  1. Deliver Enterprise AI Solutions That Produce Measurable Business Results
  • Partner directly with client stakeholders to ensure every solution delivers measurable business value through increased efficiency, reduced delivery time, improved quality, or lower operating costs. Success will be measured by successful production deployments, client adoption, engineering productivity improvements, and documented business outcomes.

  1. Transform the Software Development Lifecycle Through AI
  • Build reusable frameworks that enable engineering teams to consistently deliver higher-quality software faster and more efficiently.

  1. Build Trusted Executive Relationships While Leading Technical Delivery
  • Serve as the primary technical advisor during client engagements by facilitating discovery workshops, translating business challenges into scalable AI solutions,
  • leading technical delivery teams, and communicating effectively with both engineering organizations and executive stakeholders. Establish Client as a trusted
  • partner capable of delivering enterprise AI transformation through execution, innovation, and measurable business impact.

Subtasks

  • Design Enterprise AI Architectures
  • Design scalable AI solutions that integrate modern large language models, AI
  • agents, enterprise APIs, and intelligent automation into client environments.
  • Evaluate architectural alternatives and recommend solutions that balance
  • scalability, security, maintainability, and business value.

  • Build Production-Ready AI Applications
  • Remain actively involved in software engineering throughout the complete
  • development lifecycle by building, reviewing, testing, deploying, monitoring, and
  • supporting enterprise AI applications that meet production standards.

Lead Client Discovery and Solution Design

  • Work directly with business and technology leaders to identify opportunities where
  • AI can solve meaningful business problems. Facilitate discovery sessions, define
  • solution roadmaps, develop implementation strategies, and align technical
  • recommendations with business priorities.

Preferred Technical Environment

Candidates should demonstrate hands-on experience using modern AI engineering tools and practices, including:

  • Google Gemini
  • Cursor AI
  • Claude / Claude Code
  • Devin AI
  • Python
  • AI Agents
  • Model Context Protocol (MCP)
  • Retrieval-Augmented Generation (RAG)
  • Enterprise API Integration
  • GitHub and AI-assisted software development
  • Modern CI/CD practices
  • Experience with cloud platforms is beneficial but secondary to demonstrated success building and delivering enterprise AI solutions using AI-native engineering practices.

Definition of Success

On day one, this individual is recognized by Client leadership and enterprise clients as a trusted AI engineering leader who consistently delivers production-ready AI

solutions, transforms software engineering through AI, develops lasting client relationships, and contributes reusable assets that strengthen Clients leadership in enterprise AI consulting.

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