As a Gen AI Engineer with a strong data foundation, you will bridge the gap between traditional data architecture and cutting-edge generative AI applications. You will work closely with data scientists, software architects, and business stakeholders to design, develop, and deploy LLM-based solutions that solve complex enterprise challenges. Your day-to-day will involve building robust data pipelines, fine-tuning models, and integrating AI capabilities into existing platforms to drive measurable business outcomes and operational efficiency for our global clients.

Key Responsibilities :

- Architect and implement scalable data pipelines to support large-scale generative AI models, ensuring high data quality and low-latency access for model training.

- Design and deploy RAG (Retrieval-Augmented Generation) frameworks to enhance the accuracy and relevance of AI-generated outputs for specific business use cases.

- Collaborate with cross-functional teams to identify high-impact AI opportunities, translating business requirements into technical specifications and actionable AI roadmaps.

- Optimize model performance and inference costs by implementing efficient data indexing, vector database management, and prompt engineering strategies.

- Mentor junior engineers and lead technical discussions, fostering a culture of innovation and best practices in AI development within the organization.

Required Skillset :

- Demonstrated expertise in building and deploying production-grade AI/ML models, with a deep understanding of LLMs, transformer architectures, and NLP techniques.

- Strong proficiency in Python and data processing frameworks such as Spark, Pandas, or SQL, with a proven ability to manage large datasets in cloud environments like AWS, Azure, or GCP.

- Hands-on experience with vector databases (e.g., Pinecone, Milvus, Weaviate) and orchestration tools like LangChain or LlamaIndex.

- Exceptional communication skills, with the ability to articulate complex technical concepts to non-technical stakeholders and manage client expectations effectively.

- A Bachelor's or Master's degree in Computer Science, Data Science, or a related quantitative field, reflecting a strong analytical foundation.

- Ability to thrive in a hybrid work environment in Pune, demonstrating self-motivation and the capacity to lead projects independently while maintaining high standards of collaboration.