AI Engineer
Wipro · Chicago · $45,000–$110,000 (stated in the posting)
Wipro Limited (NYSE: WIT, BSE: 507685, NSE: WIPRO) is a leading technology services and consulting company focused on building innovative solutions that address clients’ most complex digital transformation needs. Leveraging our holistic portfolio of capabilities in consulting, design, engineering, and operations, we help clients realize their boldest ambitions and build future-ready, sustainable businesses. With over 230,000 employees and business partners across 65 countries, we deliver on the promise of helping our customers, colleagues, and communities thrive in an ever-changing world. For additional information, visit us at www.wipro.com.Job Description
Key Responsibilities:
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.
Stay updated with the latest advancements in Generative AI, LLMs, and RAG methodologies.
Required Skills & Qualifications
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 engineering, and model evaluation.
Knowledge of containerization (Docker) and orchestration (Kubernetes).
Exposure to CI/CD pipelines and DevOps practices.