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Generative AI Technical Architect - LLM / RAG

Generative AI Technical Architect - LLM / RAG

Career Soft SolutionsBangalore
30+ days ago
Job description

About the Role :

We are looking for a highly experienced GenAI Technical Architect with strong domain expertise in Generative AI, Transformer architectures, and LLM-based solution implementation. The ideal candidate will lead technical programs and architect cutting-edge solutions using large language models (LLMs), Retrieval-Augmented Generation (RAG), and related GenAI technologies. This is a hybrid role combining deep hands-on knowledge, architecture-level thinking, and program management skills.

Key Responsibilities :

  • Architect and lead the end-to-end implementation of GenAI solutions, including LLM selection, RAG integration, knowledge retrieval, and model deployment.
  • Design and implement systems using Transformer architectures (Encoder / Decoder models), leveraging frameworks like Hugging Face, LangChain, or custom pipelines.
  • Develop, evaluate, and deploy models using both Autoencoder (BERT, RoBERTa, DistilBERT) and Autoregressive (GPT, LLaMA, Mistral, PaLM, BLOOM, Claude, CodeGen, OPT) paradigms.
  • Implement RAG (Retrieval-Augmented Generation) architecture with real-world datasets and search systems.
  • Lead LLM fine-tuning and prompt engineering for domain-specific use cases and optimized performance.
  • Utilize LangChain or similar frameworks to build intelligent pipelines and agents that interact with data and APIs.
  • Drive the design and implementation of Knowledge Graphs, integrating structured and unstructured data for enterprise knowledge systems.
  • Build and execute LLM evaluation pipelines using standard evaluation metrics like RAGAS, ROUGE, BLEU, BERTScore, etc.
  • Collaborate with cross-functional teams including data science, product management, software engineering, and stakeholders to align technical roadmaps with business objectives.
  • Mentor junior engineers and data scientists on GenAI best practices and tooling.
  • Stay up-to-date with the latest advancements in Generative AI, NLP, and ML research and incorporate them into the companys AI strategy.

Required Technical Skillset :

  • Strong expertise in Transformer architectures, including both :
  • Autoencoding models : BERT, RoBERTa, DistilBERT
  • Autoregressive models : GPT (OpenAI, GPT-J), LLaMA, Claude, Mistral, PaLM, CodeGen, BLOOM, OPT, etc.
  • Solid understanding of the differences between Autoencoder and Autoregressive models and their use cases.
  • Proven experience building and deploying RAG-based systems (e.g., using FAISS, ElasticSearch, or vector DBs like Pinecone, Weaviate).
  • Proficiency with LangChain for orchestrating LLM applications.
  • Demonstrated experience in fine-tuning LLMs for custom datasets or tasks.
  • Strong understanding of ML Ops and GenAI Ops pipelines, from experimentation to deployment.
  • Experience in AI / ML development lifecycle, including data preparation, model training, evaluation, and monitoring.
  • Exposure to Knowledge Graph design and implementation is highly desirable.
  • Familiarity with evaluation frameworks and scoring metrics : RAGAS, ROUGE, BLEU, BERTScore, etc.
  • Programming expertise in Python and hands-on experience with Hugging Face Transformers, OpenAI APIs, LangChain, PyTorch / TensorFlow, LLM fine-tuning libraries.
  • Knowledge of cloud-based AI platforms (AWS SageMaker, Azure ML, GCP Vertex AI) and containerization (Docker, Kubernetes).

    • (ref : hirist.tech)

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    Generative Ai Architect • Bangalore