GenAI Engineer

Role: Gen-AI Engineer

Responsibilities:

• Lead the design and development of Gen-AI solutions, integrating them with business intelligence platforms to deliver new analytical capabilities
• Collaborate with business stakeholders to translate Business needs into technical requirements.
• Design and implement robust data models, including semantic layers and knowledge graphs, to establish clear relationships between structured and unstructured data.
• Collaborate with Data Engineering team to define optimized and efficient pipelines for Metadata ingestion and Data Processing.
• Develop and implement advanced prompt engineering strategies and Agentic RAG systems to ensure accurate, context-aware responses from Gen-AI models.
• Design and develop Agentic AI systems to enable autonomous decision making tasks.
• Monitor and evaluate model performance, ensuring continuous improvement in output quality, relevance, and user experience.
• Ensure responsible and ethical AI development, including bias mitigation, transparency, and compliance with data governance policies.
• Integrate Gen-AI models with existing BI tools, databases, and APIs to enable On-demand BI Reporting and conversational analytics.
• Conduct research on emerging Gen-AI trends, especially in enterprise analytics, and implement innovative methodologies.
• Documentation and version management of all Sprint Artefacts

Technical Skills / Experience:

Essential:

• Expertise in Gen-AI model development, fine-tuning, prompt engineering, and developing RAG architecture.
• Strong Python skills experience with PyTorch or TensorFlow.
• Strong proficiency in dimensional modeling (star/snowflake schemas), data warehousing concepts, and semantic layer design.
• Ability to design, implement, and leverage knowledge graphs to represent complex data relationships using Neo4J/AWS Neptune
• Hands-on experience with BI platforms (e.g., Tableau, Power BI) and their integration with AI systems.
• Experience with web scraping libraries like BeautifulSoup, Scrapy, or Selenium.
• Understanding of multi-agent systems and various communication architectures (e.g., MCP, Agent2Agent communication).
• Experience with LLM orchestration, or agent-based frameworks like AutoGen, Crew AI etc.

Desirable:

• Working experience with Gen-AI cloud platforms such as AWS Bedrock/Databricks Mosaic AI.
• Knowledge of MLOps and CI/CD for ML workflows.
• Experience in Automobile Engineering Datasets.

Behavioral

• Excellent interpersonal skills
• Amazing Team player and self-motivated individual
• Creativity and ability to bring in innovative ideas for Kaizen and solving everyday problems