Gen AI Engineer

Job Description: Generative AI Engineer

Position Overview:

We are seeking a highly skilled and innovative Generative AI Engineer to join our team. The ideal candidate will have hands-on experience with cutting-edge AI technologies, focusing on Retrieval-Augmented Generation (RAG), fine-tuning large language models (LLMs), building intelligent agents, and leveraging frameworks such as LangChain and LangGraph. This role will involve developing robust AI-driven solutions by integrating multi-agent systems, graph databases, and vector databases.

Key Responsibilities:

    •    Design, implement, and optimize Retrieval-Augmented Generation (RAG) systems to enhance the performance of AI applications.

    •    Fine-tune Large Language Models (LLMs) for specific use cases, ensuring high-quality outputs tailored to business needs.

    •    Develop and deploy intelligent AI agents and multi-agent systems to address complex real-world problems.

    •    Build scalable workflows using tools such as LangChain and LangGraph for orchestrating AI-powered pipelines.

    •    Integrate and manage Vector Databases (VectorDB) for efficient retrieval and similarity search in high-dimensional spaces.

    •    Work with Graph Databases (GraphDB) to model and query complex relationships between data points for enhanced decision-making.

    •    Collaborate with cross-functional teams to understand business requirements and translate them into technical implementations.

    •    Stay updated on the latest advancements in AI and propose innovative approaches to improve existing solutions.

    •    Conduct performance analysis and continuously optimize AI models and systems.

Required Qualifications:

    •    Bachelor’s or Master’s degree in Computer Science, Data Science, Artificial Intelligence, or a related field.

    •    Proven experience in working with RAG architectures and fine-tuning large-scale LLMs (e.g., GPT, LLaMA, Falcon).

    •    Proficiency in designing, developing, and managing AI-powered agents and multi-agent systems.

    •    Hands-on experience with LangChain, LangGraph, and similar frameworks for building AI pipelines.

    •    Strong knowledge of Vector Databases (e.g., Pinecone, Weaviate, Milvus) and their applications in AI systems.

    •    Familiarity with Graph Databases (e.g., Neo4j, ArangoDB) for modeling and querying complex relationships.

    •    Strong programming skills in Python and proficiency in AI/ML libraries and frameworks (e.g., PyTorch, TensorFlow).

    •    Excellent problem-solving skills, attention to detail, and the ability to work collaboratively in a fast-paced environment.

Preferred Qualifications:

    •    Experience with cloud platforms (AWS, GCP, Azure) for deploying AI systems.

    •    Knowledge of emerging trends and tools in generative AI and large language models.