181 Pinecone Jobs - Page 8

About the Role: We are seeking a highly motivated and technically proficient AI Agent Development Engineer to join our advanced AI team. In this role, you will design, build, and deploy intelligent, autonomous AI agents that leverage Generative AI , Reinforcement Learning , and Natural Language Processing (NLP) to perform complex, dynamic tasks across diverse domains. You will work at the forefront of AI agent architecture , integrating reasoning, memory, tool usage, and multi-step decision-making capabilities using state-of-the-art libraries and frameworks. Key Responsibilities: Design, develop, and deploy autonomous AI agents for real-world task automation and decision-making and orchestration. Integrate and fine-tune LLMs (Large Language Models) for goal-oriented, tool-using agents. Implement memory-augmented reasoning, retrieval-augmented generation (RAG), and multi-agent coordination. Work with vector databases to store and retrieve contextual memory and knowledge. Optimize agent performance using Reinforcement Learning frameworks and human feedback. Collaborate with cross-functional teams to integrate AI agents into applications and services. Monitor, test, and maintain AI pipelines in production environments. Required Skills & Experience: Strong programming skills in Python (C# or R is a plus). Proven experience in building and deploying AI agents or LLM-based applications . Hands-on expertise in: AI Agent Frameworks: LangChain, AutoGPT, BabyAGI, CrewAI, AgentGPT LLMs & Generative AI: OpenAI (GPT-3.5/4), Hugging Face Transformers, Anthropic Claude, Cohere Vector Search & Memory: Pinecone, FAISS, ChromaDB, Weaviate Reinforcement Learning: OpenAI Gym, Stable-Baselines3, Ray RLlib NLP & Language Tools: spaCy, NLTK, TextBlob Modeling & Deployment: TensorFlow, PyTorch, Keras, Scikit-learn, MLflow APIs & UI Frameworks: Flask, FastAPI, Streamlit, Gradio DevOps: Docker, Git, CI/CD workflows, Kubernetes, Terraform Preferred Qualifications: Experience with agent orchestration tools like LangGraph , ReAct, or Toolformer. Exposure to real-time or asynchronous multi-agent systems. Familiarity with prompt engineering, context management, and RAG pipelines. Contributions to open-source agent/LLM projects or research publications in AI/ML. Why Join Us? Be part of an AI-first product company solving real-world automation and decision-making challenges. Work with a team of AI innovators and contribute to cutting-edge research and applications.

About the Role: We are seeking a highly motivated and technically proficient AI Agent Development Engineer to join our advanced AI team. In this role, you will design, build, and deploy intelligent, autonomous AI agents that leverage Generative AI , Reinforcement Learning , and Natural Language Processing (NLP) to perform complex, dynamic tasks across diverse domains. You will work at the forefront of AI agent architecture , integrating reasoning, memory, tool usage, and multi-step decision-making capabilities using state-of-the-art libraries and frameworks. Key Responsibilities: Design, develop, and deploy autonomous AI agents for real-world task automation and decision-making and orchestration. Integrate and fine-tune LLMs (Large Language Models) for goal-oriented, tool-using agents. Implement memory-augmented reasoning, retrieval-augmented generation (RAG), and multi-agent coordination. Work with vector databases to store and retrieve contextual memory and knowledge. Optimize agent performance using Reinforcement Learning frameworks and human feedback. Collaborate with cross-functional teams to integrate AI agents into applications and services. Monitor, test, and maintain AI pipelines in production environments. Required Skills & Experience: Strong programming skills in Python (C# or R is a plus). Proven experience in building and deploying AI agents or LLM-based applications . Hands-on expertise in: AI Agent Frameworks: LangChain, AutoGPT, BabyAGI, CrewAI, AgentGPT LLMs & Generative AI: OpenAI (GPT-3.5/4), Hugging Face Transformers, Anthropic Claude, Cohere Vector Search & Memory: Pinecone, FAISS, ChromaDB, Weaviate Reinforcement Learning: OpenAI Gym, Stable-Baselines3, Ray RLlib NLP & Language Tools: spaCy, NLTK, TextBlob Modeling & Deployment: TensorFlow, PyTorch, Keras, Scikit-learn, MLflow APIs & UI Frameworks: Flask, FastAPI, Streamlit, Gradio DevOps: Docker, Git, CI/CD workflows, Kubernetes, Terraform Preferred Qualifications: Experience with agent orchestration tools like LangGraph , ReAct, or Toolformer. Exposure to real-time or asynchronous multi-agent systems. Familiarity with prompt engineering, context management, and RAG pipelines. Contributions to open-source agent/LLM projects or research publications in AI/ML. Why Join Us? Be part of an AI-first product company solving real-world automation and decision-making challenges. Work with a team of AI innovators and contribute to cutting-edge research and applications.

AI Software Engineer Location : Hyderabad - Hybrid Notice Period : 0 to 30 days Looking for Senior Fullstack AI Engineer with Python, AI/ML, GenAI, LLM, and RAG combined with frontend technologies, who can build and deploy complex, end-to-end AI applications. Core Responsibilities End-to-End AI Application Development: Design, develop, and deploy full-stack applications that integrate Generative AI and Large Language Models (LLMs). This includes building both the AI-powered backend services and the user-facing interfaces. Backend & AI Engineering: Use Python as the primary language to build robust APIs (RESTful, GraphQL) that serve AI models. Implement Retrieval-Augmented Generation (RAG) systems to enhance LLM performance and ground responses in specific, private data. Frontend Development: Create intuitive and responsive user interfaces using technologies like React, Angular, or Vue.js. This ensures that the user can effectively interact with and benefit from the powerful AI models running on the backend. System Architecture & Optimization: Architect scalable and high-performance solutions. The role involves designing the overall system, from data pipelines for AI models to cloud deployment strategies on platforms like AWS, Azure, or GCP. Mentorship and Leadership: As a senior engineer, you'll be expected to mentor junior team members, conduct code reviews, and contribute to the team's technical strategy and best practices. Key Skills and Qualifications Python: Extensive experience with Python and its AI/ML libraries, such as PyTorch, TensorFlow, and Hugging Face. Generative AI & LLMs: Hands-on experience with GenAI models, prompt engineering, fine-tuning, and integrating various LLMs (e.g., GPT-4, Llama, Gemini). RAG: Practical experience in building and optimizing RAG pipelines, including working with vector databases like Pinecone or ChromaDB. Frontend: Proficiency in JavaScript/TypeScript and a modern frontend framework like React. Full Stack: Experience in building full-stack applications and understanding of microservices architecture and cloud-native development. Please refer to the Company Profile: https://www.maantic.com/

• We are looking for a good Python Developer with Knowledge of Machine learning and deep learning framework • Take care of entire prompt life cycle like prompt design, prompt template creation, prompt tuning/optimization for various GenAI base models Required Candidate profile • Design and develop prompts suiting project needs • Stakeholder management across business and domains as required for the projects • Evaluating base models and benchmarking performance

Were looking for a skilled Generative AI Developer to build agentic AI solutions using Dify.ai or similar platforms (LangChain, LlamaIndex, Haystack). Youll design and implement intelligent, autonomous AI agents and workflows that solve real business problems. Key Responsibilities Develop agentic AI workflows with Dify.ai, LangChain, or LlamaIndex Build and integrate autonomous AI agents and RAG pipelines with vector databases (Milvus, Pinecone, Qdrant, FAISS, Weaviate) Integrate LLMs (GPT, Claude, LLaMA, Mistral, Gemini, etc.) into business solutions Extend platforms via APIs, plugins, and custom backend logic (Python) Collaborate with product and engineering teams to deliver scalable AI applications Deploy solutions with Docker (Kubernetes a plus) Required Skills 4 to 9 years in software engineering or AI/ML development Practical experience with agentic AI workflows (Dify.ai, LangChain, LlamaIndex, Haystack, etc.) Strong Python skills; experience with vector databases & RAG Familiarity with React or TypeScript (for UI/workflows) API integration and deployment with Docker

Job Overview: We are looking for a highly skilled AI & Agentic Developer to design, build, and deploy intelligent autonomous systems. This role involves developing AI-powered agents that can perceive, reason, and act independently, leveraging LLMs, reinforcement learning, and multi-agent systems. You will work on cutting-edge AI frameworks like LangChain, AutoGen, CrewAI, and MLOps pipelines for scalable deployment. Key Responsibilities: AI & Machine Learning Development: Develop, train, and fine-tune machine learning (ML) and deep learning (DL) models. Implement LLMs, NLP, reinforcement learning (RL), and computer vision (CV) models. Optimize retrieval-augmented generation (RAG) systems with vector databases (FAISS, Pinecone, Chroma). Work on multimodal AI systems integrating text, image, and audio processing. Agentic AI Systems Development: Build autonomous AI agents that can make decisions, learn from feedback, and interact with environments. Implement multi-agent frameworks using LangChain, CrewAI, AutoGen, BabyAGI, MetaGPT. Integrate AI agents with APIs, databases, and enterprise applications for real-world deployment. Software Engineering & MLOps: Design and deploy AI models using Docker, Kubernetes, and CI/CD pipelines. Implement MLOps workflows for continuous training, monitoring, and model retraining. Optimize AI solutions for cloud platforms (AWS, Azure, GCP) and edge computing. AI Governance & Security: Implement AI safety measures, including adversarial defense and bias mitigation. Ensure compliance with AI regulations (GDPR, HIPAA, SOC 2) and ethical AI principles. Secure AI agents against prompt injection, model poisoning, and adversarial attacks. Required Skills & Qualifications: Technical Skills: Strong programming skills in Python, Java, or R. Expertise in machine learning frameworks (TensorFlow, PyTorch, Scikit-Learn). Experience with LLMs & NLP (Hugging Face, OpenAI API, BERT, GPT, Claude). Proficiency in multi-agent frameworks (LangChain, CrewAI, AutoGen). Knowledge of reinforcement learning (PPO, A3C, DDPG, SAC). Experience with vector databases (FAISS, Pinecone, Chroma) and knowledge graphs. Strong foundation in MLOps, cloud AI services (AWS, Azure AI, Google Vertex AI). Soft Skills: Strong analytical and problem-solving skills. Ability to work in a fast-paced, cross-functional team. Excellent communication and documentation skills. Preferred Qualifications: Masters. in Computer Science, AI, or Data Science. Certifications in AI/ML (AWS ML Specialist, Google ML Engineer, Microsoft AI Engineer). Experience with autonomous systems, robotics, or digital twins. 5-7 years of similar or equivalent experience. Why Join Us Work on the cutting edge of AI & autonomous agents. Be part of a team driving AI innovation for real-world impact.