Role Overview :

As a GenAI Engineer, you will design, build, and optimize AI applications powered by LLMs. You will work closely with cross-functional teams to integrate AI capabilities into products and services, ensuring high performance, scalability, and usability.

Key Responsibilities :

- Develop GenAI Applications : Design, develop, and deploy applications leveraging LLMs and generative AI techniques.

- Prompt Engineering & Optimization : Craft effective prompts and optimize models for specific business use cases to improve performance and output quality.

- Build Scalable Solutions : Implement robust AI pipelines using modern frameworks and ensure solutions can scale effectively.

- Data Handling : Utilize tools such as Pandas and other data manipulation libraries to process and prepare data for AI models.

- Collaboration : Work closely with product managers, data scientists, and engineers to integrate AI capabilities into business applications.

- Model Monitoring & Troubleshooting : Continuously monitor AI model performance, troubleshoot issues, and implement improvements for better accuracy and efficiency.

Required Skills & Experience :

- Strong hands-on experience in Generative AI (GenAI) and Large Language Models (LLMs).

- Proficiency with LangChain or other Agentic AI frameworks.

- Strong Python programming skills, including experience with data handling libraries like Pandas.

- Solid understanding of AI/ML concepts, including real-world applications and deployment.

- Experience with prompt engineering and AI model optimization.

- Ability to design and implement scalable AI solutions in a production environment.

Nice to Have :

- Familiarity with AI deployment frameworks (e.g., MLflow, FastAPI, or Dockerized AI apps).

- Exposure to cloud AI services (AWS Sagemaker, Azure OpenAI, or GCP Vertex AI).

- Knowledge of conversational AI, chatbots, or multi-agent AI systems.

- Understanding of performance evaluation metrics for LLMs and GenAI models.