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.

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.

Opportunity to work on cutting-edge AI projects with meaningful real-world applications.
Collaborative and inclusive work culture.
Flexible work environment and competitive compensation.

AI Engineer

Key skills