AI Solutions Developer

3 days ago


bikaner, India beBeeArtificial Full time

Job Title: AI Solutions ArchitectDescriptionWe are seeking an experienced Ai Solutions Architect to lead the development and scaling of cutting-edge Ai solutions involving Large Language Models (LLMs), Retrieval Augmented Generation (RAG) systems, artificial intelligence agents, and autonomous workflows. As a key member of our team, you will play a pivotal role in designing architecture, building scalable pipelines, and enabling production-grade Ai systems that deliver tangible impact.This is a highly technical position that requires deep expertise in Python, cloud-native Ai systems, vector databases, orchestration frameworks, and production Machine Learning (ML).Key ResponsibilitiesArchitect and build scalable LLM-powered applications, including chatbots, RAG systems, and Ai decision-support tools.Develop autonomous agents and multi-agent systems for internal and client needs.Implement AIOps frameworks to monitor and improve production Ai systems.Build and optimize data pipelines, ML workflows, APIs, and backend services using Python & SQL.Deploy scalable systems using AWS, Docker/Kubernetes, CI/CD, and Infrastructure as Code (IaC) tools.Collaborate with cross-functional teams to define requirements and deliver Ai capabilities at scale.Mentor engineers and contribute to organizational Ai strategy.Stay updated on emerging LLM frameworks, agentic workflows, and ML infrastructure advancements.RequirementsBachelor's/Master's in Computer Science, Engineering, or a related field6+ years of experience in Ai/ML Engineering with real-world production systemsStrong experience developing and scaling LLM apps, RAG, agents, and Ai-driven appsExcellent programming skills in Python & SQLExperience with AWS, Kubernetes, Docker, CI/CD, IaCExperience with vector databases (FAISS, Pinecone, Chroma, etc.)Strong understanding of software architecture and system designExcellent communication and team collaboration skillsNice-to-Have SkillsExperience with real-time or event-driven architecturesExposure to LangChain, LangGraph, CrewAI, or agent frameworksExperience with MCP or a2a protocolsExperience leading or mentoring junior engineers



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