Urgent! Generative AI Technical Architect - LLM/RAG Job Opening In Bengaluru – Now Hiring Career Soft Solutions
<p><p><b>About the Role:</b><br/><br/></p><p>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.<br/><br/><b>Key Responsibilities :</b><br/><br/></p><p>- Architect and lead the end-to-end implementation of GenAI solutions, including LLM selection, RAG integration, knowledge retrieval, and model deployment.<br/><br/></p><p>- Design and implement systems using Transformer architectures (Encoder/Decoder models), leveraging frameworks like Hugging Face, LangChain, or custom pipelines.<br/><br/></p><p>- Develop, evaluate, and deploy models using both Autoencoder (BERT, RoBERTa, DistilBERT) and Autoregressive (GPT, LLaMA, Mistral, PaLM, BLOOM, Claude, CodeGen, OPT) paradigms.<br/><br/></p><p>- Implement RAG (Retrieval-Augmented Generation) architecture with real-world datasets and search systems.<br/><br/></p><p>- Lead LLM fine-tuning and prompt engineering for domain-specific use cases and optimized performance.<br/><br/></p><p>- Utilize LangChain or similar frameworks to build intelligent pipelines and agents that interact with data and APIs.<br/><br/></p><p>- Drive the design and implementation of Knowledge Graphs, integrating structured and unstructured data for enterprise knowledge systems.<br/><br/></p><p>- Build and execute LLM evaluation pipelines using standard evaluation metrics like RAGAS, ROUGE, BLEU, BERTScore, etc.<br/><br/></p><p>- Collaborate with cross-functional teams including data science, product management, software engineering, and stakeholders to align technical roadmaps with business objectives.<br/><br/></p><p>- Mentor junior engineers and data scientists on GenAI best practices and tooling.<br/><br/></p><p>- Stay up-to-date with the latest advancements in Generative AI, NLP, and ML research and incorporate them into the companys AI strategy.<br/><br/><b>Required Technical Skillset :</b><br/><br/></p><p>- Strong expertise in Transformer architectures, including both:<br/><br/></p><p>- Autoencoding models: BERT, RoBERTa, DistilBERT<br/><br/></p><p>- Autoregressive models: GPT (OpenAI, GPT-J), LLaMA, Claude, Mistral, PaLM, CodeGen, BLOOM, OPT, etc.<br/><br/></p><p>- Solid understanding of the differences between Autoencoder and Autoregressive models and their use cases.<br/><br/></p><p>- Proven experience building and deploying RAG-based systems (e.g., using FAISS, ElasticSearch, or vector DBs like Pinecone, Weaviate).<br/><br/></p><p>- Proficiency with LangChain for orchestrating LLM applications.<br/><br/></p><p>- Demonstrated experience in fine-tuning LLMs for custom datasets or tasks.<br/><br/></p><p>- Strong understanding of ML Ops and GenAI Ops pipelines, from experimentation to deployment.<br/><br/></p><p>- Experience in AI/ML development lifecycle, including data preparation, model training, evaluation, and monitoring.<br/><br/></p><p>- Exposure to Knowledge Graph design and implementation is highly desirable.<br/><br/></p><p>- Familiarity with evaluation frameworks and scoring metrics: RAGAS, ROUGE, BLEU, BERTScore, etc.<br/><br/></p><p>- Programming expertise in Python and hands-on experience with Hugging Face Transformers, OpenAI APIs, LangChain, PyTorch/TensorFlow, LLM fine-tuning libraries.<br/><br/></p><p>- Knowledge of cloud-based AI platforms (AWS SageMaker, Azure ML, GCP Vertex AI) and containerization (Docker, Kubernetes).</p><br/></p> (ref:hirist.tech)
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Unlock Your Generative AI Potential: Insight & Career Growth Guide
Real-time Generative AI Jobs Trends in Bengaluru, India (Graphical Representation)
Explore profound insights with Expertini's real-time, in-depth analysis, showcased through the graph below. This graph displays the job market trends for Generative AI in Bengaluru, India using a bar chart to represent the number of jobs available and a trend line to illustrate the trend over time. Specifically, the graph shows 114877 jobs in India and 4978 jobs in Bengaluru. This comprehensive analysis highlights market share and opportunities for professionals in Generative AI roles. These dynamic trends provide a better understanding of the job market landscape in these regions.
Great news! Career Soft Solutions is currently hiring and seeking a Generative AI Technical Architect LLM/RAG to join their team. Feel free to download the job details.
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The fundamental ethical values are:The average salary range for a Generative AI Technical Architect LLM/RAG Jobs India varies, but the pay scale is rated "Standard" in Bengaluru. Salary levels may vary depending on your industry, experience, and skills. It's essential to research and negotiate effectively. We advise reading the full job specification before proceeding with the application to understand the salary package.
Key qualifications for Generative AI Technical Architect LLM/RAG typically include Computer Occupations and a list of qualifications and expertise as mentioned in the job specification. Be sure to check the specific job listing for detailed requirements and qualifications.
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