AI Engineer

 Lead the design and development of scalable Generative AI solutions using LLMs
• Define and implement architectures for RAG, agentic, multi-agent, and multimodal systems
• Review and guide solution designs to ensure alignment with AI CoE standards and enterprise architecture
• Mentor and guide developers on GenAI patterns, tools, and best practices
• Develop end-to-end AI solutions using Python
• Design, test, and optimize prompt engineering strategies
• Build and manage embeddings, vector search, and semantic retrieval pipelines
• Develop applications using LangChain and monitor, evaluate, and debug workflows using LangSmith
• Integrate LLMs with enterprise systems, APIs, and structured/unstructured data sources
• Implement agent-based and multi-agent workflows for task orchestration and automation
• Work with multimodal models involving text, documents, and images
• Work closely with the AI CoE to align on AI frameworks, reusable components, and architectural standards
• Contribute to enterprise GenAI accelerators, reference architectures, and best practices
• Support governance, security, responsible AI, and compliance requirements
• Share learnings, patterns, and improvements across teams to drive consistency and adoption
• Apply deep understanding of LLM capabilities, limitations, and optimization techniques
• Implement techniques such as RAG, tool/function calling, memory, and agents
• Evaluate and recommend appropriate models (OpenAI, Azure OpenAI, open-source models)
• Ensure performance, scalability, cost optimization, and reliability of AI solutions