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# AI Engineer

- **Company:** Wipro Limited
- **Location:** Chicago, IL, United States
- **Experience:** Experienced
- **Salary:** $45,000.0 - $110,000.0
- **Contract:** Permanent contract
- **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Amazon Web Services, Microsoft Azure, Data Transformation, DevOps, Distributed Systems, Python (Programming Language), Machine Learning, Performance Tuning, Software Engineering, Google Cloud, Cloud Platform System, Data Ingestion, Retrieval-Augmented Generation, Transfer Learning, Large Language Models, Model Validation, Generative AI, Fastapi, Containerization, Kubernetes, Api Design, Data Pipelines, Docker
- **Published:** October 26, 2026
- **Apply:** https://www.indeed.com/viewjob?jk=0e91119c8d6e7546

## About the Role

8+ years of professional experience in software development and system design.

Strong proficiency in Python and experience with FastAPI for API development.

Hands-on experience with Generative AI frameworks and RAG architectures.

Solid understanding of system and architecture design principles for distributed applications.

Experience deploying solutions on any major cloud platform (AWS, Azure, GCP).

Familiarity with vector databases, embedding models, and retrieval pipelines.

Strong problem-solving skills and ability to work in a fast-paced environment.

Preferred Qualifications

Experience with LLM fine-tuning, prompt engineer ing, and model evaluation.

Knowledge of containerization (Docker) and orchestration (Kubernetes).

Exposure to CI/CD pipelines and DevOps practices.

Mandatory Skills: AI Cognitive .

Experience: 3-5 Years .

## Description

Architect and develop Generative AI applications using RAG frameworks for enterprise-scale solutions.

Design and implement robust system architectures for AI -driven platforms ensuring scalability, security, and performance.

Build and optimize APIs using FastAPI for seamless integration with AI models and data pipelines.

Collaborate with cross-functional teams to integrate AI solutions into existing systems and workflows.

Implement data ingestion, preprocessing, and retrieval mechanisms for large-scale knowledge bases.

Ensure compliance with best practices for cloud deployment (AWS, Azure, or GCP).

Conduct performance tuning and optimization of AI models and APIs.