Agentic AI Engineer

Job description

**Job Summary** The Agentic AI Engineer will be responsible for designing, developing, and deploying AI-driven solutions leveraging large language models (LLMs), diffusion models, and other generative frameworks. The role involves collaborating closely with data scientists, software engineers, and business teams to create intelligent, context-aware applications that enhance automation, creativity, and decision-making across the enterprise. **Key Responsibilities** Design, fine-tune, and deploy large language models (LLMs) and other generative models for specific business use cases. • Build and optimize prompt engineering and model interaction strategies for improved output accuracy and relevance. • Develop APIs, pipelines, and integrations to embed generative AI capabilities into products and workflows. • Collaborate with data engineers to ensure high-quality, domain-relevant datasets for model training and evaluation. • Implement responsible AI principles, including bias mitigation, explainability, and data governance. • Monitor model performance and continuously refine models through feedback loops and retraining. • Stay up to date with emerging trends in AI research, frameworks (e.g., LangChain, Hugging Face, OpenAI API), and open-source tools. • Contribute to internal knowledge sharing and best practices for scalable AI deployment. **Skill Requirements** o Proficiency in Python and frameworks such as PyTorch or TensorFlow. o Experience in SQL, Machine Learning, Big Dat and other Databases. o Experience with LLM APIs (OpenAI, Anthropic, Gemini, etc.) and vector databases (Pinecone, FAISS, Weaviate). o Familiarity with prompt engineering, model fine-tuning, and reinforcement learning from human feedback (RLHF). o Strong understanding of NLP, deep learning, and data pipeline design. o Exposure to cloud platforms (AWS, Azure, GCP) and MLOps tools for model deployment. o Strong problem-solving and analytical thinking.