AI SAAS DEVELOPER
Indexed description
This role combines AI application development, prompt engineering, backend integration, and production deployment while contributing to scalable AI product development.
Responsibilities
- Design and develop AI-powered applications using Large Language Models (OpenAI, Anthropic, Gemini, or similar).
- Build conversational AI solutions, intelligent assistants, and AI automation workflows.
- Develop prompt engineering strategies to improve AI response quality and business outcomes.
- Integrate AI services into web applications using REST APIs and Python-based backend services.
- Design NLP pipelines for text analysis, information extraction, semantic search, and document understanding.
- Collaborate with product teams to translate business requirements into AI-driven solutions.
- Participate in product architecture discussions and AI solution design.
- Optimize AI performance through prompt refinement, retrieval techniques, and evaluation methodologies.
- Develop scalable backend services using Python and FastAPI (or similar frameworks).
- Work with Git, version control, Agile development methodologies, and CI/CD pipelines.
- Deploy AI applications using cloud platforms such as AWS, Azure, or Google Cloud.
- Monitor AI system performance and continuously improve model outputs and user experience.
- Document AI solutions and maintain technical documentation.
- Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Computational Linguistics, Data Science, Software Engineering, or a related field.
- Proven working experience in software development (2-4 years).
- Knowledge of computational linguistics or Natural Language Processing.
- Experience designing AI workflows for customer engagement and business automation.
- Understanding of semantic analysis, language modelling, and prompt optimization.
- Familiarity with vector search, embeddings, and knowledge retrieval.
- Exposure to MLOps practices and AI model deployment.
- Large Language Models (LLMs)
- Prompt Engineering
- Conversational AI
- AI Workflow Design
- Retrieval-Augmented Generation (RAG)
- AI Automation
- Natural Language Processing (NLP)
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