2 Llm Orchestration Jobs

locationsBengaluru, India posted onPosted 4 Days Ago job requisition idR-462134 About this role: Wells Fargo is seeking a Software Engineer. In this role, you will: Participate in low to moderately complex initiatives and projects associated with the technology domain, including installation, upgrades, and deployment efforts Identify opportunities for service quality and availability improvements within the technology domain environment Design, code, test, debug, and document for low to moderately complex projects and programs associated with technology domain, including upgrades and deployments Review and analyze technical assignments or challenges that are related to low to medium risk deliverables and that require research, evaluation, and selection of alternative technology domains Present recommendations for resolving issues or may escalate issues as needed to meet established service level agreements Exercise some independent judgment while also developing understanding of given technology domain in reference to security and compliance requirements Provide information to technology colleagues, internal partners, and stakeholders Required Qualifications: 2+ years of software engineering experience, or equivalent demonstrated through one or a combination of the following: work experience, training, military experience, education Desired Qualifications: Work as a Generative AI engineer developing enterprise-scale AI applications Design, implement, and optimize LLM-based solutions using state-of-the-art frameworks Lead Gen AI initiatives focused on developing intelligent agents and conversational systems Design and build robust LLM interfaces and orchestration pipelines Develop evaluation frameworks to measure and improve model performance Implement prompt engineering techniques to optimize model outputs Integrate Gen AI capabilities with existing enterprise applications Build and maintain frontend interfaces for AI applications Strong proficiency in Python/Java and LLM orchestration frameworks (LangChain, LangGraph) Basic Knowledge of model context protocols, RAG architectures, and embedding techniques Experience with model evaluation frameworks and metrics for LLM performance Proficiency in frontend development with React.js for AI applications Experience with UI/UX design patterns specific to AI interfaces Experience with vector databases and efficient retrieval methods Knowledge of prompt engineering techniques and best practices Experience with containerization and microservices architecture Strong understanding of semantic search and document retrieval systems Working knowledge of both structured and unstructured data processing Experience with version control using GitHub and CI/CD pipelines Experience working with globally distributed teams in Agile scrums Job Expectations: Understanding of enterprise use cases for Generative AI Knowledge of responsible AI practices and ethical considerations Ability to optimize AI solutions for performance and cost Well versed in MLOps concepts for LLM applications Staying current with rapidly evolving Gen AI technologies and best practices Experience implementing security best practices for AI applications

We are seeking a highly skilled and motivated Senior Data Scientist with 56 years of experience to drive the development of intelligent AI systems. This role requires extensive hands-on experience with Large Language Models (LLMs) , strong background in Agentic AI , Machine Learning , and Python programming . You will work on designing autonomous agents, building scalable ML pipelines, and integrating advanced LLM-powered solutions into real-world products. Key Responsibilities: Architect and implement agentic AI systems that use LLMs for autonomous reasoning, planning, and multi-step task execution. Lead the development, fine-tuning, evaluation, and deployment of Large Language Models (LLMs) using frameworks like Hugging Face Transformers, LangChain, LLM orchestration tools, and vector databases. Develop ML models using supervised, unsupervised, and reinforcement learning techniques, and integrate them into production environments. Design and build end-to-end machine learning pipelines, including data ingestion, feature engineering, training, and deployment. Optimize model performance and latency in real-world applications and implement model monitoring and retraining strategies. Collaborate with cross-functional teams including product, engineering, and business to translate AI capabilities into product features. Mentor junior data scientists and contribute to the team's technical excellence and innovation. Required Skills & Experience: 56 years of professional and relevant experience in data science, AI, or machine learning roles. Proven hands-on experience with LLMs, including fine-tuning, prompt engineering, and RAG (Retrieval-Augmented Generation) pipelines. Deep expertise in Python and ML libraries such as scikit-learn, PyTorch, TensorFlow, and transformers. Strong understanding of agentic AI principles, autonomous agents, and task orchestration. Experience with cloud platforms (AWS, GCP, or Azure) and scalable infrastructure for deploying AI models. Exposure to API development, ML model serving, and integration with real-time systems. Excellent communication and collaboration skills in cross-functional environments. Educational Qualification: Bachelor of Technology (B.Tech) in Computer Science, Data Science, Artificial Intelligence, or a related field from a recognized institution. Preferred Qualifications: Contributions to open-source AI/ML projects or research publications related to LLMs or agent-based systems. Familiarity with LangChain, AutoGPT, CrewAI, or other agent orchestration frameworks. Experience with vector databases (e.g., FAISS, Pinecone) and knowledge of semantic search. Understanding of multi-agent collaboration, goal decomposition, and planning architectures.