LETITBEX AI
Website:
letitbexai.com
Job details:
About LetitbexAI
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 - Agentic Developer
Experience: 4 to 6 Years
Notice Period: Can be considered up 15 Days
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
Hybrid Bengaluru.
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.
Required
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 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.
Preferred
- 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
Click on Apply to know more.