As an AI Engineer, you will play a pivotal role in designing, developing, and deploying advanced AI solutions, with a strong focus on Natural Language Processing (NLP), Large Language Models (LLMs), and Multi-Modal Generative AI.
You will work closely with data scientists, product managers, engineers, and other stakeholders, and build scalable, production-grade AI solutions that address customer needs and enable operational excellence.
Key Responsibilities:
- AI Solution Development:
- Design, develop, and optimize AI algorithms and models tailored to business needs, ensuring scalability and performance.
- Develop APIs and services to make AI functionalities accessible across the organization.
- Data Preparation & Processing:
- Preprocess and prepare diverse data types (PDFs, Word documents, Excel files, HTML, audio, video, and databases) for machine learning models.
- Ensure data quality, security, and readiness for AI applications.
- LLM Applications:
- Build advanced LLM applications, including Retrieval-Augmented Generation (RAG) workflows, fine-tuning, and embedding models.
- Implement reasoning and agent-based systems, leveraging tools like LangGraph, LangChain.
- Evaluate and optimize performance with techniques like RAGAS and advanced retrieval mechanisms.
- Cloud Deployment & Operations:
- Deploy AI and LLM applications to cloud infrastructure (AWS preferred).
- Manage production-grade solutions with tools like Amazon SageMaker, implementing monitoring, scaling, and visibility tools.
- Performance Monitoring & Troubleshooting:
- Track the performance of deployed AI solutions using monitoring tools and feedback mechanisms.
- Continuously improve solution quality by analyzing outputs and addressing identified issues.
- Research & Innovation:
- Stay updated on emerging AI methodologies, frameworks, and technologies.
- Incorporate cutting-edge developments into existing workflows and create reusable AI frameworks.
- Cross-Functional Collaboration:
- Work with stakeholders such as delivery leads, product managers, and domain experts to translate business needs into actionable AI solutions.
- Collaborate with IT and cloud operations teams to ensure seamless integration and scalability of AI tools.
- Documentation & Best Practices:
- Maintain detailed documentation of AI models, processes, and workflows.
- Establish and promote best practices for AI development, deployment, and maintenance across teams.