AI Engineer

What the day will look like

• Design and implement AI solutions using Azure OpenAI, AWS Bedrock or other cloud native services
• Build scalable data pipelines, pre-process large datasets and generate vector embeddings or semantic search
• Experiment with LLM, RAG and agent-based orchestration framework
• Collaborate with cross functional team including product, data and engineering team to shape AI capabilities
• Proactively identify areas of model hallucination or bias and implement mitigation
• Develop AI services, contribute UX design discussion or better model-human interaction
• Participate in agile ceremonies, code reviews and continuous learning.

Skills and experience that will lead to success

• Implement end to end AI solution: data ingestion, pre-processing, training and deployment
• Utilize cloud Ai services (Azure/AWS) for model deployment, fine tuning and orchestration
• Build and maintain API services using C#, Python
• Design and maintain vector database and embedding pipelines using tools like Pinecone, FAISS etc.
• Implement model evaluation metrics, dashboards, and monitoring tools to detect drift and hallucinations

             Ensure security, scalability, performance in AI solution delivery