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# Software Engineer - AI Platform (Hybrid)

- **Company:** AbbVie Inc.
- **Location:** North Chicago, IL, United States
- **Experience:** Experienced
- **Salary:** $84,500.0
- **Contract:** Permanent contract
- **Skills:** Java (Programming Language), JavaScript (Programming Language), Application Programming Interfaces (APIs), Artificial Intelligence, Software Applications, Unit Testing, Cloud Computing, Continuous Integration, Information Engineering, Python (Programming Language), Machine Learning, Cloud Services, Software Engineering, TypeScript, Software Organization, Enterprise Application Integration, Retrieval-Augmented Generation, Large Language Models, Prompt Engineering, Model Validation, Generative AI, Backend, AI Platforms, Integration Tests, Software Version Control, Data Pipelines, GXP, Programming Languages
- **Published:** August 29, 2026
- **Apply:** https://www.techcareers.com/job.asp?id=3369531174&tx=UT5551TTV&pt=1&aff=0B19D771-A501-4A5E-8338-2A822B784D54&utm_source=Job%20Feed&utm_medium=textkernel&utm_campaign=DE&utm_term=0B19D771-A501-4A5E-8338-2A822B784D54

## About the Role

* Bachelor's Degree with 5 years of relevant technical experience OR Master's degree with 4 years of relevant technical experience, preferably in software engineering, data engineering, AI/ML engineering, or platform engineering.
 * Hands-on experience building or supporting software applications, APIs, cloud-based services, data pipelines, automation, or AI/ML-enabled solutions.
 * Working knowledge of modern software development practices, including source control, CI/CD, testing, monitoring, documentation, and agile delivery.
 * Experience with one or more programming languages such as Python, JavaScript/TypeScript, Java, or similar; familiarity with cloud platforms, containers, APIs, or enterprise integration patterns is preferred.
 * Interest in generative AI, LLMs, prompt engineering, retrieval-augmented generation, model evaluation, or AI platform tooling; direct enterprise AI experience is preferred.
 * Ability to learn quickly, solve ambiguous technical problems, collaborate across teams, and communicate technical concepts clearly to both technical and non-technical audiences.

## Description

Software Engineer supporting an enterprise AI platform. A hands-on engineering role with build, enhance, test, and support responsibilities of production-ready AI platform capabilities that enable teams across AbbVie to use generative AI responsibly and effectively. Work with senior engineers, product owners, architects, security partners, data teams, and business stakeholders to deliver reliable platform features, improve developer experience, support integration patterns, and contribute to governed AI solutions used across scientific, clinical, commercial, and operational areas., * Develop, test, and maintain AI platform capabilities, including APIs, backend services, user-facing workflows, automation scripts, and integration components that support enterprise generative AI use cases.

 * Contribute to reusable engineering patterns for prompt management, retrieval-augmented generation, model routing, evaluation, observability, and secure access to enterprise data and tools.
 * Work with product owners, senior engineers, architects, and business stakeholders to understand requirements, clarify user needs, estimate work, and deliver practical, maintainable solutions.
 * Support AI platform onboarding and adoption by helping teams troubleshoot issues, interpret platform guidance, improve documentation, and apply approved development patterns.
 * Assist with quality engineering activities, including unit testing, integration testing, user acceptance testing, defect resolution, and validation evidence needed for controlled enterprise environments.
 * Help operate and improve AI platform production services by monitoring reliability, investigating incidents, resolving support tickets, and identifying opportunities to simplify or automate recurring support needs.
 * Follow AbbVie standards for secure software delivery, responsible AI, privacy, GxP awareness, data protection, change management, and the software development lifecycle.
 * Communicate progress, risks, tradeoffs, and technical findings clearly to teammates and stakeholders; escalate issues appropriately and contribute to a collaborative engineering culture.


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