As an Artificial Intelligence Engineer specializing in LLMs and RAG, you will be at the forefront of building sophisticated generative AI solutions that solve complex business challenges. You will work closely with cross-functional product and engineering teams to design, deploy, and scale intelligent systems that leverage large language models to enhance user experiences and operational efficiency. Your work will directly impact how our clients process information, automate workflows, and derive actionable insights from unstructured data, making you a critical contributor to the company's AI-driven roadmap.

Key Responsibilities :

- Architect and implement robust Retrieval Augmented Generation (RAG) pipelines to improve the accuracy and relevance of AI-generated responses for enterprise applications.

- Fine-tune and optimize Large Language Models (LLMs) using frameworks like OpenAI and Gemini to meet specific domain requirements and performance benchmarks.

- Develop scalable data ingestion and processing workflows to ensure high-quality data retrieval for generative AI models.

- Collaborate with stakeholders to translate business requirements into technical AI specifications, ensuring solutions align with long-term product goals.

- Monitor and evaluate model performance, implementing iterative improvements to reduce hallucinations and latency in production environments.

- Mentor junior engineers and contribute to technical documentation to foster a culture of knowledge sharing and engineering excellence.

Required Skillset :

- Demonstrated expertise in Python programming and deep learning frameworks, with a strong foundation in Natural Language Processing (NLP) techniques.

- Proven ability to design and deploy end-to-end Generative AI solutions, specifically leveraging RAG architectures and vector databases.

- Hands-on experience integrating and customizing LLM APIs from providers such as OpenAI and Google Gemini.

- Strong analytical capabilities to troubleshoot model performance issues and optimize inference pipelines for production-scale applications.

- Excellent communication skills to articulate complex technical concepts to non-technical stakeholders and work effectively in a collaborative, high-growth environment.

- A degree in Computer Science, Data Science, or a related quantitative field, combined with 4 to 9 years of relevant industry experience.

- Ability to thrive in a hybrid or on-site work environment across Gurgaon, Delhi NCR, or Bangalore, demonstrating high adaptability to evolving project priorities.