Senior AI Engineer

We are seeking an experienced Senior AI Engineer to spearhead the development and deployment of cutting-edge AI solutions. The ideal candidate will have strong foundations 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, LangGraph, LangChain, Graph Databases, and open-source LLMs. This role involves designing and implementing advanced AI capabilities, building real-time data pipelines, integrating with modern cloud AI platforms, and mentoring junior engineers 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 in Computer Vision, NLP, and Generative AI. Fine-tune and deploy open-source large language models (LLMs) and private models for EdTech applications. Implement RAG (Retrieval-Augmented Generation) systems combining retrieval with generative models. Leverage LangGraph and LangChain for orchestration, multi-step workflows, and stateful agent design. Data Engineering & Integration:Develop and integrate real-time data pipelines and event-driven architectures using Kafka, Spark, or PySpark. Build secure, scalable, and cloud-native AI solutions using AWS Bedrock, SageMaker, Google Vertex AI, Azure ML (AML), Azure AKS, and related services. Implement MLOps/LLMOps pipelines for efficient deployment, monitoring, and scaling of AI models. AI Infrastructure & Tools:Work with modern AI toolkits and frameworks such as Hugging Face Transformers, MLflow, and Databricks. Develop prompt engineering strategies and optimize LLMs for improved accuracy and relevance. Contribute to internal AI frameworks and toolkits for accelerated adoption across teams. Leadership:Mentor and guide junior engineers, fostering innovation and skill development. Collaborate with cross-functional teams to align AI strategies with business goals. Promote best practices in coding, testing, documentation, and model lifecycle management.

Bachelor's or Master's degree in Computer Science, AI, Data Science, or related fields. 3+ years in AI/ML system development and deployment in production environments. Proven track record of designing AI systems in cloud environments and working with data-intensive pipelines.