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 .\n\nThis 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.\n\nKey Responsibilities\nAI Model Development:\nDesign, train, and deploy AI models for diverse use cases in Computer Vision, NLP, and Generative AI .\nFine-tune and deploy open-source large language models (LLMs) and private models for EdTech applications.\nImplement RAG (Retrieval-Augmented Generation) systems combining retrieval with generative models.\nLeverage LangGraph and LangChain for orchestration, multi-step workflows, and stateful agent design.\nData Engineering & Integration:\nDevelop and integrate real-time data pipelines and event-driven architectures using Kafka, Spark, or PySpark .\nBuild secure, scalable, and cloud-native AI solutions using AWS Bedrock, SageMaker, Google Vertex AI, Azure ML (AML), Azure AKS , and related services.\nImplement MLOps/LLMOps pipelines for efficient deployment, monitoring, and scaling of AI models.\nAI Infrastructure & Tools:\nWork with modern AI toolkits and frameworks such as Hugging Face Transformers, MLflow, and Databricks .\nDevelop prompt engineering strategies and optimize LLMs for improved accuracy and relevance.\nContribute to internal AI frameworks and toolkits for accelerated adoption across teams.\nLeadership:\nMentor and guide junior engineers, fostering innovation and skill development.\nCollaborate with cross-functional teams to align AI strategies with business goals.\nPromote best practices in coding, testing, documentation, and model lifecycle management.\n\nRequirements\nExperience:\n3+ years in AI/ML system development and deployment in production environments.\nProven track record of designing AI systems in cloud environments and working with data-intensive pipelines .\nTechnical Skills:\nStrong Python proficiency (async programming, multi-step workflows).\nExpertise in machine learning and deep learning frameworks: TensorFlow, PyTorch, Scikit-learn .\nProficiency with tools like Hugging Face, LangChain, LangGraph, OpenAI API, and Bedrock API .\nHands-on experience with ETL/ELT workflows , data transformations, and SQL (data modeling, normalization, optimization) .\nKnowledge of RAG architectures, Graph Databases, and MCP (Model Context Protocol) .\nFamiliarity with CI/CD pipelines , containerization ( Docker, Kubernetes ), and cloud AI platforms ( AWS, GCP, Azure ).\nDomain Knowledge:\nUnderstanding of EdTech standards like LTI, xAPI, QTI , and SCORM.\nFamiliarity with adaptive learning systems and educational content pipelines.\nKnowledge of workflows in K-12, higher education, and corporate learning environments is a strong plus.\nSoft Skills:\nExceptional leadership and team mentoring abilities.\nStrong problem-solving skills and excellent communication for technical and non-technical stakeholders.\nEducation:\nBachelor’s or Master’s degree in Computer Science, AI, Data Science, or related fields.\n\nWhy Join Us\nOpportunity to lead AI initiatives that shape the future of education technology.\nWork in a collaborative, mission-driven environment with a focus on innovation.\nEngage with impactful projects and cutting-edge AI technologies.\nCompetitive salary, benefits, and opportunities for professional growth.\n\nEmployee Benefits\nHealth Insurance: Employee + Spouse + Two Children + Parents\nGPA Coverage for Employee\nHybrid Work Model\nCompliance: PF and Gratuity