AI Engineer

• Design and implement scalable RAG pipelines to enable contextual, high-quality responses using enterprise knowledge bases.
• Evaluate and integrate Frontier LLMs /Open source LLM and APIs for specific tasks, ensuring optimal performance and efficiency.
• Build autonomous agent workflows using tools like CrewAI, LangGraph, Autogen, or OpenAI SDK.
• Develop and optimize prompts, chains, and multi-agent systems.
• Stay updated on the latest in the GenAI ecosystem and make recommendations for internal adoption.
• Collaborate with stakeholders to understand use cases, define solution architectures, and iterate prototypes into production-ready systems.
• Ensure responsible AI practices, including data privacy, model explainability, and
  compliance.

Required Skills & Experience

• 6 to 7 years of overall industry experience with at least 1–2 years in Generative AI /LLM-focused projects.
• Strong understanding of Frontier LLMs and their application across domains.
• Hands-on experience in IDE’s such as Cursor
• Hands-on experience building Retrieval-Augmented Generation systems using vector databases (like FAISS, Weaviate, or Pinecone).
• Working knowledge of CrewAI, LangGraph, Autogen, or similar agent orchestration frameworks.
• Proficiency in Python, with experience using libraries like LangChain, Transformers, and OpenAI SDKs.
• Familiarity with API integrations, asynchronous task handling, and cloud-native
  deployment (Azure).
• Excellent problem-solving and analytical skills.
• Strong written and verbal communication skills.