About The Role

Role Overview

We are seeking a skilled AI Engineer to design, develop, deploy, and optimize AI-powered solutions that drive business value. The ideal candidate will have expertise in Machine Learning, Generative AI, Large Language Models (LLMs), and MLOps, with experience building scalable AI applications in cloud environments.

Key Responsibilities

Design, develop, and deploy AI/ML models and Generative AI solutions.
Build intelligent applications leveraging Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and Agentic AI frameworks.
Develop and optimize machine learning pipelines for training, evaluation, and deployment.
Implement data preprocessing, feature engineering, and model performance tuning.
Integrate AI solutions into enterprise applications through APIs and microservices.
Collaborate with Data Engineers, Product Managers, Architects, and business stakeholders to identify AI use cases.
Monitor model performance, accuracy, drift, and scalability in production environments.
Implement MLOps best practices for model versioning, deployment, and monitoring.
Ensure AI solutions comply with security, privacy, and responsible AI guidelines.
Stay current with emerging AI technologies and industry best practices.

Required Skills & Qualifications

Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, or a related field.
4+ years of experience in AI/ML development.
Strong programming skills in Python .
Hands-on experience with machine learning frameworks such as:
TensorFlow
PyTorch
Scikit-learn
Experience with Generative AI , LLMs , and prompt engineering.
Knowledge of RAG , vector databases, embeddings, and semantic search.
Experience with REST APIs, microservices, and application integration.
Strong understanding of data structures, algorithms, and software engineering principles.
Experience working with SQL and NoSQL databases.
Familiarity with Agile development methodologies.

Preferred Skills

Experience with Azure OpenAI, Vertex AI, Google Gemini, Anthropic Claude, or OpenAI models.
Exposure to LangChain, LangGraph, LlamaIndex, CrewAI, or similar Agentic AI frameworks.
Experience with MLOps tools such as MLflow, Kubeflow, or Vertex AI Pipelines.
Knowledge of Docker, Kubernetes, and CI/CD pipelines.
Experience with cloud platforms such as GCP, Azure, or AWS .

Technical Skills

AI & Machine Learning

Machine Learning
Deep Learning
NLP
Computer Vision
Generative AI
Large Language Models (LLMs)
Prompt Engineering
Retrieval-Augmented Generation (RAG)

Programming & Frameworks

Python
TensorFlow
PyTorch
Scikit-learn
LangChain
LangGraph
LlamaIndex

Cloud & MLOps

Vertex AI / Azure AI Services / AWS SageMaker
MLflow
Docker
Kubernetes
GitHub Actions / Azure DevOps

Databases

PostgreSQL
MongoDB
BigQuery
Pinecone
Weaviate
ChromaDB

Key Competencies

AI Solution Design
Model Development & Optimization
Problem Solving
Innovation Mindset
Analytical Thinking
Stakeholder Management
Communication & Collaboration

Nice to Have

Google Professional Machine Learning Engineer, Azure AI Engineer, or AWS ML Certification.
Experience building enterprise-scale AI copilots and chatbots.
Exposure to Responsible AI, AI Governance, and Model Explainability.
Experience in Retail, E-commerce, Supply Chain, or Customer Analytics domains.