Generative AI Engineer

Responsibilities AI Application Development: Design and develop intelligent chatbots and conversational AI systems for various business applications Build and deploy social media analysis tools using natural language processing and sentiment analysis Implement AI-powered content generation and analysis systems Create and maintain AI agents for task automation and workflow optimization LLM Integration & Optimization: Set up, configure, and fine-tune Large Language Models (LLMs) for specific use cases Implement prompt engineering techniques to optimize model performance Integrate various LLM APIs (OpenAI, Anthropic, Google, etc.) into applications Develop custom model pipelines and orchestration workflows Security & Governance: Implement AI security guardrails and content filtering systems Design and deploy safety mechanisms for AI-generated content Ensure compliance with AI ethics and responsible AI practices Monitor and mitigate potential risks in AI applications Technical Infrastructure: Build and maintain vector databases for semantic search and retrieval systems Implement Retrieval-Augmented Generation (RAG) architectures Work with Model Context Protocol (MCP) for enhanced AI capabilities Design scalable AI systems and optimize performance for production environments Framework & Tool Utilization: Develop applications using LangChain and LangSmith frameworks Build custom AI workflows and chains for complex use cases Integrate with various AI/ML platforms and services Maintain and optimize existing AI codebases Qualifications Bachelor’s degree in computer science, AI/ML, Data Science, or related technical field Relevant certifications in AI/ML or cloud platforms are a plus. Continuous learning mindset with up-to-date knowledge of AI trends Required Skills Programming: Proficiency in Python with experience in AI/ML libraries GenAI Frameworks: Hands-on experience with LangChain, LangSmith, or similar frameworks LLM Integration: Experience setting up and working with various LLMs (GPT, Claude, Gemini, etc.) Vector Databases: Knowledge of Pinecone, Weaviate, Chroma, or similar vector storage solutions AI/ML Libraries: Familiarity with HuggingFace Transformers, OpenAI API, Anthropic API Data Processing: Experience with pandas, numpy, and data preprocessing techniques APIs & Integration: RESTful API development and third-party service integration Preferred Skills 1-2 years of hands-on experience in Generative AI or related AI/ML fields Proven track record of building and deploying AI applications in production Experience with at least 2-3 major GenAI projects or use cases Experience with cloud platforms (AWS, GCP, Azure) for AI/ML workloads Knowledge of containerization (Docker, Kubernetes) for AI application deployment Background in social media analytics and content moderation Experience with multi-modal AI applications (text, image, audio) Knowledge of AI agent frameworks and autonomous systems Understanding of enterprise AI governance and compliance requirements Strong problem-solving abilities and analytical thinking Excellent communication skills for technical and non-technical stakeholders Ability to work in fast-paced, iterative development environments Collaborative mindset for cross-functional team projects

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