Generative AI Engineer
1 week ago
Role Overview:Looking for a Generative AI Specialist with 5-7 years of experience focusing on state-of-the-art generative AI technologies including large language models (LLMs) and agentic AI. The candidate will act as a technical mentor, engaging with clients to develop advanced generative solutions and mentor junior team members.Key Responsibilities:- Architect, fine-tune, and deploy Generative AI and LLM-based solutions for diverse industries.- Lead development of RAG pipelines, multi-agent orchestration, and generative workflows for automation.- Collaborate with clients to define problem statements, data strategies, and AI integration approaches.- Design and execute rapid prototypes and POCs using transformer-based and diffusion-based architectures.- Mentor junior engineers on LLM fine-tuning, prompt engineering, and API-based integration.- Continuously evaluate and adopt emerging open-source frameworks and foundation models (e.g., Llama, Claude, Gemini, Mistral).- Drive MLOps integration for generative AI solutions ensuring scalability, reproducibility, and compliance.Requirements:- 5–7 years of overall AI experience, with at least 2–3 years dedicated to Generative AI and LLM-based systems.- Hands-on experience building RAG, conversational, or multi-agent-based AI architectures.- Expertise in fine-tuning, prompt optimization, and LLM orchestration.- Proven success in developing generative solutions for enterprise applications.- Excellent communication and technical mentoring skills.- Bachelor’s/master’s degree in computer science, AI, or related disciplineDesired Technical Skills & Tools:- Programming: Python, LangChain, LlamaIndex, Multi Agentic Systems- LLM Frameworks: OpenAI GPT series, Hugging Face Transformers, Anthropic Claude, Mistral, Llama 3, Agnos- Generative AI Tools: LangGraph, Vector Databases (Pinecone, FAISS, Chroma), PromptLayer, LangFuse- RAG & Agent Frameworks: Haystack, Semantic Kernel, AutoGen, CrewAI- MLOps & Deployment: Docker, Kubernetes, MLflow, Vertex AI, Azure OpenAI, AWS Bedrock- Data & Integration: REST APIs, Kafka, ElasticSearch, PostgreSQL, NoSQL, Data Lakes- Other Skills: Prompt Engineering, Model Evaluation Metrics, Hallucination Control, Knowledge Graphs, Context Management- Cloud & Infra: Azure AI Studio, AWS SageMaker, GCP GenAI Studio
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