Artificial Intelligence Engineer (Lead)

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.