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Generative AI Engineer - LLM Job Opening In Bengaluru – Now Hiring LION AND ELEPHANTS CONSULTANCY PRIVATE LIMITED


Job description

<p><b>About the Role :</b><br/><br/>We are seeking a highly capable and motivated PX-Gen AI Engineer with hands-on expertise in Python, Generative AI (Gen AI), Agentic AI, and ML systems development.

The ideal candidate will be proficient in developing and deploying LLMs, building scalable APIs, and integrating cloud-native AI solutions on AWS and Azure platforms.<br/><br/>You'll be part of an advanced engineering team working on cutting-edge Gen AI systems, including agent-based architectures, model fine-tuning, LLM evaluation, and full-stack AI application delivery.<br/><br/><b>Key Responsibilities :</b><br/><br/><b>Model Fine-Tuning & Training :</b><br/><br/>- Fine-tune Large Language Models (LLMs) for specific business tasks using frameworks like PyTorch, Langchain, DSPy, etc.<br/><br/>- Improve model accuracy and efficiency through training optimization and data augmentation strategies.<br/><br/><b>Model Deployment & Integration :</b><br/><br/>- Deploy models in production using AWS or Azure, and containerize using Docker.<br/><br/>- Build cloud-native, scalable Gen AI services using offerings like Cognitive Services, API Management (APIM), App Services, and S3/Object Storage.<br/><br/><b>API Development & Web Integration :</b><br/><br/>- Build robust, RESTful APIs using FastAPI or Flask to serve ML models and LLMs.<br/><br/>- Integrate APIs with third-party systems and ensure secure, high-performance communication.<br/><br/><b>Agentic AI & LLM Evaluation :</b><br/><br/>- Develop and evaluate Agentic AI systems capable of decision-making, task orchestration, and dynamic workflow execution.<br/><br/>- Design testing and evaluation pipelines for LLMs to assess quality, coherence, latency, and use-case effectiveness.<br/><br/><b>Search & Indexing :</b><br/><br/>- Implement NLP-based search and indexing systems using tools like Elasticsearch, FAISS, or similar.<br/><br/>- Optimize information retrieval for semantic understanding and relevance scoring.<br/><br/><b>Research & Innovation :</b><br/><br/>- Stay abreast of the latest developments in Generative AI, NLP, LLM architectures, and multi-agent frameworks.<br/><br/>- Bring new ideas and innovations into existing platforms and solutions.<br/><br/><b>Mandatory Skills :</b><br/><br/>- Programming : Python (expert level)<br/><br/>- AI/ML Fundamentals : Strong foundation in ML algorithms and DL architectures<br/><br/>- Gen AI & LLMs : Langchain, LangGraph, PyTorch, DSPy<br/><br/>- Web Frameworks : FastAPI, Flask<br/><br/>- Cloud Platforms : AWS (primary), Azure (secondary)<br/><br/>- Agentic AI : Experience with multi-agent or autonomous system design<br/><br/>- DevOps Tools : Docker, API development, LLM evaluation pipelines<br/><br/><b>Skills to Evaluate (Technical Assessment) :</b><br/><br/>- Python<br/><br/>- Generative AI<br/><br/>- AWS (services for AI/ML)<br/><br/>- Agentic AI<br/><br/>- ML fundamentals<br/><br/>- Flask & FastAPI (API frameworks)<br/><br/>- PyTorch (model Skills :</b><br/><br/>- Exposure to search/indexing systems (e.g., FAISS, Pinecone, Elasticsearch)<br/><br/>- Understanding of LLMOps and Model-as-a-Service deployment practices<br/><br/>- Familiarity with SpaCy, MCP, and LangGraph<br/><br/>- Experience deploying LLMs at scale with GPU/TPU integration<br/><br/><b>Qualifications :</b><br/><br/>- Bachelor's or Master's in Computer Science, AI/ML, or a related engineering discipline<br/><br/>- 5-7 years of relevant experience in AI/ML engineering<br/><br/>- Proven track record in building Gen AI solutions for production use</p> (ref:hirist.tech)

Required Skill Profession

Computer Occupations


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