Job highlights

- Bachelor s or master s degree in computer science,AI,Data Science,or related fields.

- 2+ years of experience in team leading

- Hands-on experience with ETL / ELT workflows,data transformations,and SQL (data modeling,normalization,optimization)

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 contemporary 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.

Requirements

- Experience:

- 5+ years in AI/ML system development and deployment in production environments.

- 2+ years of experience in team leading.

- Proven track record of designing AI systems in cloud environments and working with data-intensive pipelines .

- Technical Skills:

- Strong Python proficiency (async programming, multi-step workflows).

- Expertise in machine learning and deep learning frameworks: TensorFlow, PyTorch, Scikit-learn .

- Proficiency with tools like Hugging Face, LangChain, LangGraph, OpenAI API, and Bedrock API .

- Hands-on experience with ETL/ELT workflows , data transformations, and SQL (data modeling, normalization, optimization) .

- Knowledge of RAG architectures, Graph Databases, and MCP (Model Context Protocol) .

- Familiarity with CI/CD pipelines , containerization ( Docker, Kubernetes ), and cloud AI platforms ( AWS, GCP, Azure ).

- Domain Knowledge:

- Understanding of EdTech standards like LTI, xAPI, QTI , and SCORM.

- Familiarity with adaptive learning systems and educational content pipelines.

- Knowledge of workflows in K-12, higher education, and corporate learning environments 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.

📌 Lead Engineer AI (Pune)
🏢 Academian India
📍 Pune