AI Developer and Solutions Architect

7 days ago

tiruppur, India beBeeArtificialintelligence Full time

Job Title: AI Developer and Solutions ArchitectThis is a challenging role that requires exceptional technical expertise in Artificial Intelligence (AI) and software development. As an AI developer and solutions architect, you will be responsible for designing and implementing cutting-edge AI solutions that integrate real-time and historical data to facilitate autonomous decision-making.The ideal candidate should have strong proficiency in Python programming and experience with LangChain, LangGraph, and other AI frameworks. You should also have a deep understanding of LLM architectures, prompt engineering, retrieval-augmented generation (RAG), and semantic search methodologies.Key Responsibilities: Design and implement end-to-end full-stack AI solutions that integrate real-time and historical data. Develop intelligent agents using LangChain and LangGraph, leveraging large language models (LLMs) for document authoring, semantic search, and recommendation systems. Build scalable, secure, and compliant chatbot interfaces that serve enterprise needs. Develop and maintain robust data pipelines using Python, Snowflake SQL, and various AWS-native services to ensure seamless data flow and processing. Integrate graph databases like Neo4j and vector databases to enable semantic search capabilities and contextual reasoning. Deploy scalable AI services on cloud platforms including AWS (Bedrock, Lambda, ECS), Azure AI, and GCP.Required Skills: Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, or a related technical field. 5+ years of professional software engineering experience with at least 3 years focused on AI/ML and large language model-based systems. Advanced proficiency in Python programming. Hands-on experience with LangChain, LangGraph, AutoGen, CrewAI, LlamaIndex or similar AI frameworks. Deep understanding of LLM architectures, prompt engineering, retrieval-augmented generation (RAG), and semantic search methodologies. Experience working with embedding-based search systems and graph technologies such as Neo4j and GraphRAG. Proficiency in cloud AI platforms including Azure AI, AWS (Bedrock, Lambda, ECS), and Google Cloud Platform (GCP). Strong experience with containerization and orchestration tools including Docker, Kubernetes, and infrastructure as code using Terraform. Expertise in building scalable APIs using frameworks such as FastAPI and Flask, and integrating them with enterprise systems. Familiarity with CI/CD pipelines and observability tools to ensure reliable deployment and monitoring of AI services. Knowledge of AI ethics, governance, and compliance frameworks applicable to regulated industries. Demonstrated leadership skills with experience mentoring teams and managing cross-functional collaboration.

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