Sr AI Full Stack Engineer
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Role details
Tech stack
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Job description
We are looking for a skilled and innovative AI Full Stack Engineer with strong expertise in Python, Large Language Models (LLMs), LangChain, LangGraph, Retrieval-Augmented Generation (RAG), 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. The candidate will also design modular prompt pipelines and build knowledge graphs to enhance AI reasoning capabilities., * Develop, maintain, and deploy 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.
- Design, 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 AI model inference workflows, model performance, latency, scalability, cost, and reliability.
- Implement evaluation frameworks, guardrails, security controls, and responsible AI practices.
- Collaborate with Data Scientists, ML Engineers, Product Managers, Architects, and Software Engineers to deliver AI-driven features and solutions.
- Troubleshoot, debug, and update AI components as necessary.
- Monitor and continuously improve production AI systems through feedback loops and observability tools.
- Keep abreast of the latest advancements in AI technologies and promote best practices across the team.
Requirements
Artificial Intelligence (AI), Python Programming/Scripting Language, Software Engineering, Artificial Intelligence (AI), Software Agents, Business Operations, Modeling Languages, Artificial Intelligence (AI) Agents, Memory Management, Enterprise Applications, * Strong 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.
- 7+ years in Artificial Intelligence (AI).
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