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Gen Ai Software Developer Jobs in Naperville, IL

Establish measurable approaches for evaluating the impact of AI on developer productivity, software quality and reliability, and overall speed of delivery. * Ensure autonomous engineering agents ...

Establish measurable approaches for evaluating the impact of AI on developer productivity, software quality and reliability, and overall speed of delivery. * Ensure autonomous engineering agents ...

We are engineers, AI practitioners, platform builders, thought leaders, multipliers, and coders ... Required Qualifications * 6-7 years of AI software development experience, with at least 2 years in ...

Senior AI Software Engineer

Chicago, IL · On-site

$126K - $166K/yr

Senior individual contributor on the Developer Experience (DevX) platform team, responsible for designing, building, and operating an AI-native software delivery platform across five capability ...

Collaborate with software developers and QE analysts to identify system requirements and ensure ... Use Gen AI to drive innovation and efficiency in testing responsibilities

Data Engineer - Python/AI

Addison, IL · On-site

$114K - $137K/yr

... in software engineering with strong handson development in Python * 3+ years of handson AI/ML experience , building and deploying machine learning models and Gen AI solutions using locally hosted ...

Showing results 21-40

Gen Ai Software Developer information

See Naperville, IL salary details

$47.9K

$111.7K

$165.8K

How much do gen ai software developer jobs pay per year?

As of Sep 4, 2026, the average yearly pay for gen ai software developer in Naperville, IL is $111,678.00, according to ZipRecruiter salary data. Most workers in this role earn between $89,900.00 and $129,800.00 per year, depending on experience, location, and employer.

What is a Gen AI software developer?

A Gen AI Software Developer is a professional who designs, builds, and maintains software systems that leverage generative artificial intelligence models, such as large language models (LLMs) or generative adversarial networks (GANs). Their work often involves training, fine-tuning, and deploying AI models to generate content, automate tasks, or enhance user experiences in applications. They need strong programming skills, a solid understanding of machine learning principles, and familiarity with AI frameworks. Gen AI Software Developers collaborate with data scientists, engineers, and product teams to deliver innovative AI-driven solutions. As generative AI becomes more prevalent, these developers play a key role in shaping the future of software development.

What are the key skills and qualifications needed to thrive as a Gen AI software developer, and why are they important?

To thrive as a Gen AI Software Developer, you need strong programming skills (especially in Python), a background in computer science or a related field, and expertise in machine learning and deep learning principles. Familiarity with frameworks like TensorFlow or PyTorch, experience with cloud platforms (such as AWS or Azure), and knowledge of version control systems are typically required, along with certifications in AI or data science being advantageous. Creative problem-solving, collaboration, and effective communication help developers work across technical and non-technical teams and drive innovation. These skills ensure the development of robust, scalable AI solutions that address real-world needs and integrate seamlessly within organizations.

How do Gen AI software developers typically collaborate with data scientists and product managers during the development process?

Gen AI Software Developers regularly work alongside data scientists to translate machine learning models into scalable, production-ready applications. They collaborate closely with product managers to understand user requirements and ensure that AI-powered features align with business goals. This teamwork often involves participating in cross-functional meetings, iterative feedback cycles, and joint problem-solving sessions to address technical challenges and optimize model performance. Clear communication and a shared understanding of project objectives are essential for success in this collaborative environment.

What is the difference between Gen Ai Software Developer vs Machine Learning Engineer?

AspectGen Ai Software DeveloperMachine Learning Engineer
Required CredentialsBachelor's in CS, AI, or related; experience with AI frameworksBachelor's or higher in CS, Data Science, or related; strong programming skills
Work EnvironmentTech companies, startups, AI-focused teamsResearch labs, tech firms, AI/ML departments
Employer & Industry UsageAI product development, software solutionsModel development, data analysis, AI system deployment
Common Search & ComparisonFocuses on AI application development in softwareFocuses on building and optimizing ML models

While both roles involve AI and require programming skills, Gen Ai Software Developers primarily focus on creating AI-powered software applications, whereas Machine Learning Engineers specialize in designing, building, and optimizing machine learning models. The roles often overlap but differ in their core focus and typical work environments.

What are popular job titles related to Gen Ai Software Developer jobs in Naperville, IL?

For Gen Ai Software Developer jobs in Naperville, IL, the most frequently searched job titles are:

What cities near Naperville, IL are hiring for Gen Ai Software Developer jobs?

Cities near Naperville, IL with the most Gen Ai Software Developer job openings:

Infographic showing various Gen Ai Software Developer job openings in Naperville, IL as of August 2026, with employment types broken down into 88% Full Time, 8% Part Time, and 4% Contract. Highlights an 88% Physical, 3% Hybrid, and 9% Remote job distribution, with an average salary of $111,678 per year, or $53.7 per hour.

VP, AI & Software Engineering

RR Donnelley

Chicago, IL

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 7 days ago


Key responsibilities

  • Define and lead the adoption of AI across the software development lifecycle to establish new engineering practices.

  • Build organizational capability to design, develop, and operate AI-powered business solutions, including agentic applications and workflow automation.

  • Serve as a key advisor to define and adapt the enterprise technology roadmap, engineering strategy, and architectural vision.


RR Donnelley rating

6.4

Company rating: 6.4 out of 10

Based on 134 frontline employees who took The Breakroom Quiz

36th of 52 rated marketing agency


Job description

Company Description

RRD provides a complete portfolio of marketing, packaging, print and business services to the world’s most respected brands, including 92% of the Fortune 100. The company’s proprietary technology, advanced data analytics and established expertise fuel organizational decision-making, from strategy through execution. With operations in 30 countries and over 35,000 employees, global organizations and regulated industries trust RRD to reduce complexity and drive audience connections across the entire customer journey.

Job Description

Role Mission

The Vice President of AI & Software Engineering will shape the next era of our technology organization, leading the transformation from a traditional software engineering model to an AI-native engineering organization built on modern engineering practices and intelligent automation.

This leader will drive AI across two critical dimensions: transforming how we engineer software through AI-assisted and agentic development practices, and building AI-powered solutions that create meaningful business value. The VP of Engineering will guide the evolution of our people, processes, applications, and technology platforms while honoring the strong foundation that has successfully enabled our business for more than 30 years. They will balance innovation with pragmatism by applying AI where it improves engineering effectiveness or business outcomes.

As a strategic partner to the SVP of Digital Strategy, the VP of Engineering will help define our technology vision, engineering practices, AI strategy, governance, and investment priorities while ensuring disciplined execution, operational excellence, and sound financial stewardship.

Key Responsibilities

AI-Native Software Engineering

  • Define and lead the adoption of AI across the software development lifecycle, establishing new engineering practices that combine human expertise with AI-assisted definition, design, development, and delivery.
  • Maintain a strong understanding of the rapidly evolving AI engineering landscape and continually adapt engineering practices, principles, and investment priorities as capabilities mature.
  • Establish measurable approaches for evaluating the impact of AI on developer productivity, software quality and reliability, and overall speed of delivery.
  • Ensure autonomous engineering agents operate within defined guardrails and modernization standards so generated code aligns with production and architectural expectations from the outset.
  • Architect applications and infrastructure to be “agent-ready”, systematically removing friction so automated workflows have increasingly higher-quality results over time.

AI Solution Engineering & Innovation

  • Build the organizational capability to design, develop, and operate AI-powered business solutions, including agentic applications, AI assistants, workflow automation, and operations optimization tools.
  • Establish practical patterns for integrating AI capabilities into enterprise applications and workflows, including the platforms, APIs, enterprise data, security, and observability required to operate them effectively.
  • Establish rigorous practices for evaluating AI technologies and solutions based on business value, implementation reality, cost, and risk.
  • Create an engineering model that supports our idea-to-production pipeline, providing a disciplined path for moving successful concepts into production-grade solutions.
  • Provide technical leadership on emerging AI technologies and vendors, separating realistic business value from market hype and informing build, buy, partner, and platform decisions.

Modern Software & Platform Engineering

  • Serve as a key advisor to the SVP of Digital Strategy and other business and technology leaders, helping define and adapt the enterprise technology roadmap, engineering strategy, and architectural vision.
  • Advance modular, API-first, and composable engineering patterns that support rapid business delivery and seamless AI integration.
  • Maintain responsible stewardship of core legacy platforms, making deliberate investment decisions about where to modernize, re-architect, or retain.
  • Systematically optimize codebases, environments, and data access layers so autonomous tools and human teams can develop software safely and efficiently.

Strategic Talent & Delivery Models

  • Shape the right mix of internal engineering talent, strategic partners, outsourcing, and augmentation for an AI-native organization.
  • Build and continuously develop the capabilities of the engineering organization, creating opportunities for existing talent to grow and succeed as software engineering practices and technologies evolve.
  • Identify emerging capability gaps and execute focused hiring strategies that bring critical engineering expertise into the organization.
  • Design and oversee effective support and sourcing models that maintain reliability while increasingly using automation and AI to improve efficiency.

Financial Discipline & Investment Management

  • Maintain excellence in financial discipline, managing the department budget with transparency and precision.
  • Evaluate technology investments based on measurable business and engineering outcomes rather than technology adoption alone.
  • Identify cost improvement opportunities through automation, engineering productivity, architectural efficiencies, application rationalization, optimized vendor management, and active management of cloud and AI unit economics.
  • Manage OpEx/CapEx effectively, connecting technology investments and engineering milestones to measurable financial and business outcomes.
    Qualifications
    • Bachelors Degree in Business, Computer Science, Information Systems, Industrial Management, Engineering, or related field, preferred
    • 10-14 years of technical experience with 4-6 years of direct management of staff (managers and staff) OR demonstrated ability to meet the job requirements through a comparable number of years of applicable work experience.
    • Demonstrated experience leading enterprise application modernization, including the evolution of legacy and monolithic systems toward modular, API-first, cloud-ready architectures.
    • Deep understanding of the AI software engineering landscape, with experience applying AI-assisted and agentic approaches across the software development lifecycle.
    • Demonstrated ability to establish and evolve engineering standards, architecture principles, and governance.
    • Experience leading the evolution of engineering operating models and practices across established technology organizations.
    • Strong background in OpEx/CapEx management and the ability to tie technical milestones to financial outcomes.
    • Able to consistently contribute effort, leadership, and creative thinking to solving complex and significant problems in a collaborative fashion.
    • Must be able to demonstrate an ability to work concurrently on multiple complex and sometimes ambiguous problems.
    • Able to communicate complex concepts, problems, and solutions clearly and effectively to all levels within the organization.
    • Exceptional leadership abilities with a track record of building, managing, and motivating high-performing teams that are geographically distributed.
    • Strong business acumen and ability to understand and drive business objectives.
    • Strong organizational skills, including the ability to perform well under pressure and manage multiple priorities with competing demands for resources.
    • Requires excellent communication skills with all levels of audience. Able to structure messages in keeping with the listener’s experience, background, and expectations.

    Additional Information

    RRD's current salary range for this role is $172,400 to $275,800 / year. The salary range may be adjusted based on the applicable geographic location of the hired employee, and the range may change in the future. At RRD, it is not typical for an individual to be hired at or near the top of the range for their role and compensation decisions may vary based upon, but not limited to education, skills, experience, proficiency, performance, shift and location. Depending on the role, in addition to base salary, the total compensation package may also include participation in a bonus, commission or incentive program. RRD’s benefit offerings include medical, dental, and vision coverage, paid time off, disability insurance, 401(k) with company match, life insurance and other voluntary supplemental insurance coverages, plus parental leave, adoption assistance, tuition assistance and employer/partner discounts.

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    RRD is an Equal Opportunity Employer, including disability/veterans

    At RRD, we value innovation, authenticity, and integrity. To uphold the security and fairness of our hiring process, we ask that candidates refrain from using AI tools during interviews to ensure an authentic and secure experience. We appreciate your cooperation as we work to maintain a transparent and equitable hiring process.

    All employment offers are contingent upon the successful completion of both a pre-employment background and drug screen.


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