Role Overview :

As a Gen AI Engineer at Rayosys Services, you will be at the forefront of our artificial intelligence initiatives, designing and deploying sophisticated models that solve real-world business challenges. You will work closely with cross-functional teams, including data scientists, product managers, and software architects, to translate complex requirements into scalable AI solutions. Your daily contributions will involve building robust pipelines, fine-tuning large language models, and integrating agentic workflows that directly enhance operational efficiency and user experience for our global client base.

Key Responsibilities :

- Architect and implement end-to-end Generative AI solutions, including RAG systems and LLM-based applications, to automate complex workflows for our enterprise clients.

- Design and optimize agentic AI frameworks that enable autonomous decision-making and task execution within existing software ecosystems.

- Develop and maintain high-performance data pipelines using Python to ensure seamless integration between raw data sources and vector databases.

- Collaborate with stakeholders to refine prompt engineering strategies, ensuring model outputs are accurate, context-aware, and aligned with business objectives.

- Deploy and monitor machine learning models in cloud environments, ensuring high availability, scalability, and cost-efficiency for production workloads.

- Conduct rigorous testing and evaluation of deep learning models to improve performance metrics and mitigate potential biases in AI-driven outputs.

Required Skillset :

- Demonstrated expertise in building and deploying LLM-based applications using frameworks such as LangChain, with a deep understanding of RAG architectures and vector database management.

- Proficiency in Python and deep learning libraries including PyTorch and Tensorflow to develop, train, and fine-tune machine learning models.

- Strong grasp of Natural Language Processing techniques and advanced prompt engineering methodologies to optimize model performance for specific use cases.

- Proven ability to manage data engineering tasks and cloud computing infrastructure, ensuring robust and scalable AI deployments.

- Exceptional analytical and problem-solving skills, with the ability to communicate complex technical concepts to non-technical stakeholders effectively.

- A minimum of 5 - 8 years of professional experience in software engineering or data science, with a focus on AI/ML development.

- Ability to thrive in a flexible work environment across metro locations, maintaining high levels of productivity and collaboration in hybrid or remote settings.