Design, develop, and rigorously test end-to-end Generative AI and agentic AI applications
Build and orchestrate multi-agent systems using frameworks like CrewAI, LangGraph, OpenAI Agents SDK, or Azure AI Agent Framework
Implement retrieval-augmented generation pipelines involving embedding creation, chunking, and vector indexing using FAISS, Pinecone, Chroma, or Milvus
Apply advanced prompting strategies such as Few-Shot Learning, Chain-of-Thought (CoT), ReAct, and CART to improve reliability and interpretability of model responses
Establish automated and manual testing pipelines using TruLens, LangSmith, PromptLayer, or DeepEval to evaluate model quality, accuracy, safety, and factual grounding
Seeking a passionate and skilled AI Engineer with 2–5 years of experience to build and deploy advanced AI solutions leveraging Retrieval-Augmented Generation (RAG), Large Language Models (LLMs), and multi-agent frameworks.
Responsibilities
Design, develop, and deploy GenAI solutions, with a focus on real-world production readiness.
Build and scale Retrieval-Augmented Generation (RAG) systems for enterprise use cases.
Integrate with graph-based memory and tool-using agents to enhance LLM capabilities.
Implement multi-agent orchestration and reasoning systems (e.g., AutoGen, LangGraph, custom agents).
Use LLM frameworks and libraries (e.g., LangChain, AutoGen, LangGraph etc.).
We are seeking a passionate and skilled AI Engineer with 3–7 years of experience, including a minimum of 2 years in Generative AI (GenAI), to join our AI/ML team. The AI Engineer will play a key role in building and deploying advanced AI solutions leveraging Retrieval-Augmented Generation (RAG), Large Language Models (LLMs), multi-agent frameworks, and state-of-the-art tooling.
Locations (2)
Bengaluru, Karnataka, India
India
Responsibilities
Design, develop, and deploy GenAI solutions, with a focus on real-world production readiness.
Build and scale Retrieval-Augmented Generation (RAG) systems for enterprise use cases.
Integrate with graph-based memory and tool-using agents to enhance LLM capabilities.
Implement multi-agent orchestration and reasoning systems (e.g., AutoGen, LangGraph, custom agents).
Use LLM frameworks and libraries (e.g., LangChain, AutoGen, LangGraph etc.).
AI Engineer with 3–7 years of experience, including 2+ years in Generative AI, to build and deploy GenAI solutions using RAG, LLMs, and multi-agent frameworks.
Locations (2)
Bengaluru, Karnataka, India
India
Responsibilities
Design, develop, and deploy GenAI solutions, with a focus on real-world production readiness.
Build and scale Retrieval-Augmented Generation (RAG) systems for enterprise use cases.
Integrate with graph-based memory and tool-using agents to enhance LLM capabilities.
Implement multi-agent orchestration and reasoning systems (e.g., AutoGen, LangGraph, custom agents).
Use LLM frameworks and libraries (e.g., LangChain, AutoGen, LangGraph etc.).
Requirements
Bachelor’s degree in Computer Science, Engineering, or a related field
AI Engineer with 3–7 years of experience, including a minimum of 2 years in Generative AI, to build and deploy advanced AI solutions leveraging Retrieval-Augmented Generation, LLMs, multi-agent frameworks, and state-of-the-art tooling.
Responsibilities
Design, develop, and deploy GenAI solutions
Build and scale Retrieval-Augmented Generation systems
Integrate with graph-based memory and tool-using agents
Implement multi-agent orchestration and reasoning systems
Use LLM frameworks and libraries
Requirements
Bachelor’s degree in Computer Science or Engineering