AI Engineer

Key Responsibilities

AI & Machine Learning Development

• Design, develop, and deploy AI/ML models for business use cases.
• Build and optimize machine learning pipelines from data preparation to model deployment.
• Develop predictive, classification, recommendation, and NLP solutions.
• Fine-tune and evaluate foundation models and LLMs.

Generative AI Solutions

• Design and implement Generative AI applications using LLMs.
• Develop Retrieval-Augmented Generation (RAG) solutions.
• Create prompt engineering frameworks and reusable AI workflows.
• Integrate AI copilots, chatbots, and virtual assistants into enterprise platforms.
• Implement AI governance, monitoring, and responsible AI practices.

Data Engineering & Integration

• Collaborate with Data Engineers and Data Scientists to prepare training datasets.
• Develop APIs and microservices for AI model consumption.
• Integrate AI services with enterprise systems and cloud platforms.

Model Deployment & Monitoring

• Deploy AI solutions using MLOps best practices.
• Monitor model performance, accuracy, drift, and reliability.
• Ensure scalability, security, and compliance requirements are met.

Qualifications

Required Technical Skills

AI / ML Technologies

• Machine Learning Algorithms
• Deep Learning
• Natural Language Processing (NLP)
• Generative AI
• Large Language Models (LLMs)
• Prompt Engineering
• Vector Databases

Programming Languages

• Python (Mandatory)
• SQL
• Optional: Java, JavaScript, or Scala

AI Frameworks & Libraries

• TensorFlow
• PyTorch
• Scikit-learn
• LangChain
• LlamaIndex
• Hugging Face Transformers
• OpenAI APIs / Azure OpenAI

Vector Databases

• Pinecone
• Weaviate
• ChromaDB
• FAISS

Cloud & MLOps

• Azure AI Services / Azure OpenAI
• AWS Bedrock / SageMaker
• Google Vertex AI
• MLflow
• Docker
• Kubernetes
• CI/CD Pipelines

Database Technologies

• SQL Server
• PostgreSQL
• MongoDB
• Cosmos DB

Leadership & Soft Skills

• Strong analytical and problem-solving skills.
• Excellent communication and stakeholder management.
• Ability to translate business problems into AI-driven solutions.
• Experience working in Agile/Scrum environments.
• Strong collaboration with cross-functional teams.

Preferred Qualifications

• Experience building enterprise AI assistants and chatbots.
• Hands-on experience with RAG architectures and vector search.
• Knowledge of Responsible AI, AI Safety, and AI Governance.
• Exposure to Agentic AI frameworks and autonomous AI workflows.
• Experience with Retail, E-commerce, BFSI, Healthcare, or Supply Chain domains.

Educational Qualification

• Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, or a related field.

Preferred Certifications

• Microsoft Azure AI Engineer Associate (AI-102)
• Microsoft Azure Data Scientist Associate (DP-100)
• AWS Machine Learning Specialty
• Google Professional Machine Learning Engineer
• TensorFlow Developer Certificate

Key Competencies

• Artificial Intelligence
• Generative AI
• Machine Learning
• Prompt Engineering
• LLM Development
• NLP
• RAG Architecture
• MLOps
• Data Analytics
• Innovation & Problem Solving

Responsibilities

Required Technical Skills

AI / ML Technologies

• Machine Learning Algorithms
• Deep Learning
• Natural Language Processing (NLP)
• Generative AI
• Large Language Models (LLMs)
• Prompt Engineering
• Vector Databases

Programming Languages

• Python (Mandatory)
• SQL
• Optional: Java, JavaScript, or Scala

AI Frameworks & Libraries

• TensorFlow
• PyTorch
• Scikit-learn
• LangChain
• LlamaIndex
• Hugging Face Transformers
• OpenAI APIs / Azure OpenAI

Vector Databases

• Pinecone
• Weaviate
• ChromaDB
• FAISS

Cloud & MLOps

• Azure AI Services / Azure OpenAI
• AWS Bedrock / SageMaker
• Google Vertex AI
• MLflow
• Docker
• Kubernetes
• CI/CD Pipelines

Database Technologies

• SQL Server
• PostgreSQL
• MongoDB
• Cosmos DB

Leadership & Soft Skills

• Strong analytical and problem-solving skills.
• Excellent communication and stakeholder management.
• Ability to translate business problems into AI-driven solutions.
• Experience working in Agile/Scrum environments.
• Strong collaboration with cross-functional teams.

Preferred Qualifications

• Experience building enterprise AI assistants and chatbots.
• Hands-on experience with RAG architectures and vector search.
• Knowledge of Responsible AI, AI Safety, and AI Governance.
• Exposure to Agentic AI frameworks and autonomous AI workflows.
• Experience with Retail, E-commerce, BFSI, Healthcare, or Supply Chain domains.

Educational Qualification

• Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, or a related field.

Preferred Certifications

• Microsoft Azure AI Engineer Associate (AI-102)
• Microsoft Azure Data Scientist Associate (DP-100)
• AWS Machine Learning Specialty
• Google Professional Machine Learning Engineer
• TensorFlow Developer Certificate

Key Competencies

• Artificial Intelligence
• Generative AI
• Machine Learning
• Prompt Engineering
• LLM Development
• NLP
• RAG Architecture
• MLOps
• Data Analytics
• Innovation & Problem Solving