Lead Engineer AI

ESP Engineered; Pune District; On-site; INR 3,000,000 - 5,400,000; Full time

Benefits offered by this job

Health Insurance

Job summary

Academian, a carve-out of Intraedge Inc, is seeking a Lead AI Engineer to spearhead AI development for EdTech. You will work on CV, NLP, and Generative AI, leveraging open-source LLMs, RAG, LangGraph, and LangChain.

The role involves building real-time data pipelines, deploying on cloud platforms (AWS, GCP, Azure), and mentoring engineers to deliver scalable AI products.

Qualifications

• 5+ years in AI/ML system development and deployment in production environments.
• 2+ years of experience in team leading.
• Strong proficiency with Python and modern ML/DL frameworks (TensorFlow, PyTorch).
• Experience with cloud AI platforms (AWS, GCP, Azure).
• Familiarity with RAG architectures, LangChain/LangGraph, and data pipelines.

Responsibilities

• Design, train, and deploy AI models for CV, NLP, and Generative AI use cases.
• Fine-tune and deploy open-source LLMs and private models for EdTech.
• Implement RAG systems combining retrieval with generative models.
• Develop real-time data pipelines and event-driven architectures (Kafka, Spark).
• Build cloud-native AI solutions and ML operations pipelines (MLOps/LLMOps).
• Mentor junior engineers and collaborate with cross-functional teams.

Skills

Python proficiency

Leadership & mentoring

Problem solving

Communication skills

Education

Bachelor’s or master’s degree in computer science / AI / Data Science

Tools

TensorFlow

PyTorch

Scikit-learn

Hugging Face

LangChain

LangGraph

OpenAI API

Bedrock API

Docker

Kubernetes

Apache Spark

Kafka

Databricks

Job description

We are seeking an experienced Lead 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

• 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.
• 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.
• 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.
• 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.
• 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.
• 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.
• 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.
• 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.

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.
• 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).
• 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.
• 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.
• 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.
• Bachelor’s or master’s degree in computer science, AI, Data Science, or related fields.
• 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.

Why Join Us

• Opportunity to lead AI initiatives that shape the future of education technology.
• Work in a collaborative, mission-driven environment with a focus on innovation.
• Engage with impactful projects and cutting-edge AI technologies.
• Competitive salary, benefits, and opportunities for professional growth.

Employee Benefits

• Health Insurance: Employee + Spouse + Two Children + Parents

Academian, a carve-out of the 22-year-old Intraedge Inc (www.intraedge.com) , is a rapidly growing service, product, and learning development company specializing in EdTech. With 500+ team members, we deliver innovative solutions spanning LMS, CMS, custom software, cloud architecture, and digital learning.

At Academian, you’ll work on transformative projects that improve learning experiences globally. From K-12 to higher education, publishing, and workforce development, we are redefining education technology with a strong commitment to DEIB and innovation.