Data Scientist

LetitbexAI is a fast-growing AI-driven technology company focused on building intelligent, scalable, and enterprise-grade solutions. We work at the intersection of AI, data engineering, cloud, and business transformation, helping organizations unlock real value from artificial intelligence.

Position: Data Scientist

Experience: 4 to 6 Years

Notice Period: Can be considered up 15 Days

We are looking for a Data Scientist 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.

What You’ll Do

• 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.
  

What You'll Need

• 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 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.
  

• 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