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 modern 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.