About the Role :

We are looking for a highly experienced AI Engineer to design, develop, and deploy enterprise-grade AI and Generative AI solutions. The role requires strong hands-on engineering expertise along with the ability to lead complex AI initiatives and guide engineering teams.

Key Responsibilities :

- Design, develop, and deploy production-grade AI/ML solutions.
- Develop Generative AI applications using LLMs and contemporary AI frameworks.
- Build RAG-based applications using enterprise data and knowledge sources.
- Develop AI agents and agentic workflows for complex enterprise use cases.
- Implement model inference, evaluation, optimization, and monitoring pipelines.
- Integrate AI models with enterprise applications through APIs and microservices.
- Develop NLP, machine learning, and deep learning solutions based on business requirements.
- Work with structured and unstructured data for AI applications.
- Build prompt engineering, model evaluation, grounding, and retrieval strategies.
- Implement vector search, embeddings, semantic search, and knowledge retrieval.
- Deploy AI models and applications in scalable production environments.
- Optimize model performance, latency, scalability, and infrastructure utilization.
- Implement AI application security, governance, monitoring,



and observability.
- Conduct technical POCs and evaluate new AI models and frameworks.
- Collaborate with data engineers, software engineers, architects, and product teams.
- Mentor senior engineers and establish engineering best practices.
- Troubleshoot complex technical issues across AI applications and platforms.

Required Skills :

- 10-12 years of experience in software engineering, AI/ML engineering, or related technology roles.
- Strong proficiency in Python.
- Extensive experience with Machine Learning, Deep Learning, NLP, and Generative AI.
- Strong hands-on experience with LLMs and LLM-based applications.
- Experience with RAG, embeddings, vector databases, prompt engineering, and AI agents.
- Experience with AI/ML frameworks and model development libraries.
- Strong software engineering fundamentals including APIs, microservices, databases, and distributed systems.
- Experience deploying AI solutions into production environments.
- Strong understanding of MLOps, model lifecycle, monitoring, and evaluation.
- Experience working with cloud-based AI/ML environments.
- Strong debugging, architecture, problem-solving, and technical leadership capabilities.

📌 Infosys - AI Engineer - LLM/RAG (India)
🏢 Infosys
📍 India