Artificial Intelligence Engineer

Role Overview We are seeking an experienced AI Technical Lead to spearhead the development and deployment of cutting-edge AI solutions. The ideal candidate will possess a strong foundation in AI algorithms, hands-on expertise with machine learning and deep learning frameworks, and a forward-thinking approach to leveraging emerging AI technologies like AGENTIC AI, RAG, Graph Databases, and open-source LLMs. This role also involves guiding the team to deliver scalable, efficient, and impactful AI products aligned with the EdTech domain. Key Responsibilities AI Model Development : Design, train, and deploy AI models for diverse use cases, including: Computer Vision : Image recognition, object detection, segmentation etc. Natural Language Processing (NLP) : Text classification, summarization, question-answering systems etc. Generative AI : Fine-tuning and deploying open-source large language models (LLMs) and Private Models. RAG (Retrieval-Augmented Generation) : Implement AI systems combining retrieval with generative models. Optimize AI models for performance, scalability, and accuracy using core algorithms (regression, KNN, SVM, etc.). Open-Source LLM Development : Develop and fine-tune open-source LLMs to cater to domain-specific needs. Deploy open-source LLMs effectively in production environments, ensuring scalability and low latency. Explore and implement open-source tools and frameworks like Hugging Face, LangChain, and Transformer libraries. Integration & Architecture : Integrate AI solutions with Vector/Graph db for advanced data relationships and queries. Implement and manage MLOps / LLMOps pipelines for efficient deployment, monitoring, and scaling of AI models. Leadership : Mentor and guide junior engineers, fostering innovation and skill development. Collaborate with cross-functional teams, including product management, data engineering, and software development, to align AI strategies with business goals. Infrastructure : Leverage cloud AI platforms (AWS SageMaker, Google Vertex AI, Azure AI) for scalable solutions. Adopt open-source frameworks and tools (e.G., TensorFlow, PyTorch, Hugging Face) for experimentation and development. Best Practices : Establish robust practices for coding, testing, and documenting AI solutions. Stay at the forefront of AI research and emerging trends like AGENTIC AI, RAG, and open-source LLM development. Requirements Experience 4+ years of experience in AI/ML. Proven expertise in designing and deploying AI solutions in production environments. Technical Skills Strong proficiency in machine learning frameworks (TensorFlow, PyTorch, Scikit-learn). Hands-on experience with tools like Hugging Face, OpenAI API, and Google AI tools. In-depth understanding of core ML algorithms (regression, KNN, clustering, etc.) and deep learning models . Familiarity with open-source LLM development and deployment Experience with RAG architectures , Graph Databases , and LLMOps practices. Expertise in CI/CD pipelines, containerization (Docker, Kubernetes), and cloud AI platforms (AWS, Google Cloud, Azure). Domain Knowledge Familiarity with EdTech standards (LTI, xAPI, QTI) and adaptive learning systems is a strong plus. Soft Skills Exceptional leadership and team mentoring abilities. Strong problem-solving skills and excellent communication for technical and non-technical stakeholders. Education Bachelor’s or Master’s degree in Computer Science, AI, Data Science, or related fields. Why Join Us Drive AI initiatives shaping the future of education technology. Work in a collaborative, innovation-focused environment. Competitive salary, comprehensive benefits, and opportunities for professional growth.