Description

Key Responsibilities:

• Develop and maintain AI applications using Python. • Design and implement chain-of-thought prompt pipelines utilizing LangChain for modular, scalable AI workflows. • Build and integrate knowledge graphs with LangGraph to improve data connectivity and reasoning. • Collaborate with data scientists, ML engineers, and product teams to deliver AI-driven features. • Optimize AI model inference workflows to enhance performance and scalability. • Troubleshoot, debug, and update AI components as necessary. • Keep abreast of the latest advancements in AI technologies and promote best practices across the team. ole Descriptions: We are seeking an innovative AI Engineer with strong expertise in Large Language Models (LLMs), Python development, LangChain, LangGraph, and Agentic AI frameworks. The ideal candidate will design, develop, deploy, and optimize enterprise-grade Generative AI solutions, intelligent agents, and AI-powered applications that drive business value and operational efficiency.Key ResponsibilitiesDesign, build, and deploy AI applications leveraging LLMs such as GPT, Claude, Gemini, Llama, and other foundation models.Develop Agentic AI solutions capable of autonomous reasoning, planning, tool execution, and decision-making.Build multi-agent systems using LangGraph and LangChain frameworks.Implement RAG (Retrieval-Augmented Generation) architectures using vector databases and enterprise knowledge sources.Develop prompt engineering, context management, memory, and workflow orchestration strategies.Integrate AI agents with enterprise applications, APIs, databases, and business processes.Optimize model performance, latency, scalability, cost, and reliability.Implement evaluation frameworks, guardrails, security controls, and responsible AI practices.Collaborate with Product Managers, Data Scientists, Architects, and Software Engineers to deliver AI-driven solutions.Monitor and continuously improve production AI systems through feedback loops and observability tools.Required Technical SkillsStrong proficiency in Python and software engineering best practices.Hands-on experience with LLMs and Generative AI technologies.Experience building applications using LangChain and LangGraph.Deep understanding of Agentic AI, multi-agent systems, planning, memory, and tool-calling architectures.Experience implementing RAG, semantic search, embeddings, and vector databases.Knowledge of prompt engineering, fine-tuning, model evaluation, and AI governance.Experience with REST APIs, microservices, and cloud-native architectures.Familiarity with Git, CI/CD pipelines, and DevOps practices.Experience with cloud platforms such as Azure, AWS, or Google Cloud. Essential Skills: We are seeking an innovative AI Engineer with strong expertise in Large Language Models (LLMs), Python development, LangChain, LangGraph, and Agentic AI frameworks. The ideal candidate will design, develop, deploy, and optimize enterprise-grade Generative AI solutions, intelligent agents, and AI-powered applications that drive business value and operational efficiency.Key ResponsibilitiesDesign, build, and deploy AI applications leveraging LLMs such as GPT, Claude, Gemini, Llama, and other foundation models.Develop Agentic AI solutions capable of autonomous reasoning, planning, tool execution, and decision-making.Build multi-agent systems using LangGraph and LangChain frameworks.Implement RAG (Retrieval-Augmented Generation) architectures using vector databases and enterprise knowledge sources.Develop prompt engineering, context management, memory, and workflow orchestration strategies.Integrate AI agents with enterprise applications, APIs, databases, and business processes.Optimize model performance, latency, scalability, cost, and reliability.Implement evaluation frameworks, guardrails, security controls, and responsible AI practices.Collaborate with Product Managers, Data Scientists, Architects, and Software Engineers to deliver AI-driven solutions.Monitor and continuously improve production AI systems through feedback loops and observability tools.Required Technical SkillsStrong proficiency in Python and software engineering best practices.Hands-on experience with LLMs and Generative AI technologies.Experience building applications using LangChain and LangGraph.Deep understanding of Agentic AI, multi-agent systems, planning, memory, and tool-calling architectures.Experience implementing RAG, semantic search, embeddings, and vector databases.Knowledge of prompt engineering, fine-tuning, model evaluation, and AI governance.Experience with REST APIs, microservices, and

Key Skills

Education

Bachelor's degree