AI Engineer

Wipro•Chicago, IL

About The Position

Wipro Limited is a technology services and consulting company that develops solutions for clients’ digital transformation needs. The AI Engineer will architect and develop enterprise-scale Generative AI applications using retrieval-augmented generation (RAG) frameworks, design scalable and secure AI platform architectures, and build APIs for integrating AI models and data pipelines. The role includes collaborating with cross-functional teams to incorporate AI solutions into existing systems, implementing data ingestion and retrieval for large knowledge bases, and deploying solutions on a major cloud platform. The engineer will also tune and optimize AI models and APIs and keep current with developments in Generative AI, large language models, and RAG methodologies. The expected compensation ranges from $45,000 to $110,000. Final compensation depends on factors including location, applicable minimum-wage obligations, skills, and relevant experience. The role is eligible for Wipro’s standard benefits, including medical and dental benefit options, disability insurance, paid time off (including sick leave), and other paid and unpaid leave options. Employment in some roles may be conditioned on successful completion of a post-offer drug screening, subject to applicable state law.

Requirements

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 a major cloud platform: AWS, Azure, or GCP.
Familiarity with vector databases, embedding models, and retrieval pipelines.
Strong problem-solving skills and ability to work in a fast-paced environment.
Mandatory skill: AI Cognitive.
The posting also lists 3–5 years of experience.

Nice To Haves

Experience with LLM fine-tuning, prompt engineering, and model evaluation.
Knowledge of containerization with Docker and orchestration with Kubernetes.
Exposure to CI/CD pipelines and DevOps practices.

Responsibilities

Architect and develop enterprise-scale Generative AI applications using RAG frameworks.
Design and implement robust system architectures for AI-driven platforms, ensuring scalability, security, and performance.
Build and optimize APIs using FastAPI for 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.
Follow best practices for cloud deployment on AWS, Azure, or GCP.
Tune and optimize AI models and APIs.
Stay updated on advancements in Generative AI, LLMs, and RAG methodologies.