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Data Scientist

Data ScientistData ScientistFull TimeRemoteMid LevelTeam 501-1,000H1B SponsorCompany SiteLinkedIn

Location

Worldwide

Posted

8 days ago

Salary

0

Seniority

Mid Level

Job Description

Data Scientist

CAI

Role Description We are looking for a Data Scientist - Agentic Developer to design cutting-edge AI solutions and autonomous systems focused on agentic workflows and generative AI technologies. This position will be full-time and remote . - Design, develop, and deploy multi-agent systems and agentic applications using frameworks like AutoGen, LangGraph, CrewAI, or similar. - Build intelligent workflow orchestration systems that enable autonomous decision-making and task execution. - Implement Agent-to-Agent (A2A) communication protocols and Model Context Protocol (MCP) for seamless agent collaboration. - Develop automation solutions using OpenAPI standards for integration with enterprise systems. - Create self-healing, adaptive workflows that optimize business processes autonomously. - Use ML, deep learning, and Generative AI tools to design, evangelize, and implement state-of-the-art solutions. - Define and implement best practices for building, testing, and deploying scalable AI solutions, with a focus on generative models and LLMs using proprietary or open-source models. - Drive successful business outcomes by designing and building cloud-hosted Generative AI solutions. - Work closely with internal teams to integrate RAG workflows, agent-based systems, and automation frameworks into applications. - Design and implement architectural solutions for Information Retrieval using RAG, Vector DBs, and Knowledge Graphs. - Work with public cloud (AWS) and on-premises infrastructure for deploying LLMs, agents, and orchestration systems. - Evaluate, build, and fine-tune ML models and LLMs to solve complex business problems. - Stay abreast of latest developments in agentic AI, autonomous systems, language models, and generative AI technologies. Qualifications - BE, Master's or Ph.D. in Computer Science, Artificial Intelligence, Machine Learning, or equivalent practical experience. - 4-8 years of overall technical experience with 0-2 years of hands-on experience in Generative AI and LLM technologies. - 1+ years of experience building agentic systems, workflow automation, or autonomous AI applications. - Deep hands-on experience with agentic frameworks (AutoGen, LangGraph, CrewAI, Agency Swarm, or similar). - Strong knowledge of workflow orchestration tools and patterns (Temporal, Airflow, Prefect, or similar). - Expertise in OpenAPI standards, Agent-to-Agent (A2A) protocols, and Model Context Protocol (MCP). - Experience designing multi-agent architectures with memory, planning, and tool-use capabilities. - Knowledge of agent evaluation, testing frameworks, and observability patterns. - Proven track record of deploying and optimizing LLM models for inference in production environments. - Extensive experience with LLM orchestration frameworks (LangChain, LlamaIndex required). - Hands-on experience with Amazon Bedrock, SageMaker JumpStart, and other cloud-based LLM platforms. - Expertise in RAG architectures, Fine-tuning techniques, and Prompt Engineering. - Deep understanding of Vector Databases (Pinecone, Weaviate, Milvus, ChromaDB) and Knowledge Graphs. - Expert in NLP techniques and deep learning libraries (Transformer models, LSTM, BiLSTM, CNN, BERT, GPT, T5). - Proficiency with ML frameworks: TensorFlow, PyTorch, Hugging Face Transformers, scikit-learn. - Strong programming skills in Python (required), plus JavaScript/TypeScript or Node.js. - Deep understanding of data structures, algorithms, and system design patterns. - Hands-on experience in MLOps/LLMOps including data pipelines, model training/refinement, validation, drift management, and serving. - Experience with containerization (Docker, Kubernetes) and CI/CD pipelines for ML systems. - Knowledge of monitoring, logging, and observability tools for production AI systems. Requirements - Experience with function calling, tool use, and external API integration in agent systems. - Knowledge of reinforcement learning and agent training methodologies. - Familiarity with semantic reasoning, planning algorithms (ReAct, Chain-of-Thought, Tree-of-Thoughts). - Experience with graph databases (Neo4j, Neptune) and ontology design. - Contributions to open-source AI/ML projects. - Publications or patents in AI/ML domain. Benefits - Ability to safely and successfully perform the essential job functions. - Sedentary work that involves sitting or remaining stationary most of the time with occasional need to move around the office to attend meetings, etc. - Ability to conduct repetitive tasks on a computer, utilizing a mouse, keyboard, and monitor. Reasonable Accommodation Statement If you require a reasonable accommodation in completing this application, interviewing, completing any pre-employment testing, or otherwise participating in the employment selection process, please direct your inquiries to application.accommodations@cai.io or (888) 824 – 8111.

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