Role

We are seeking a skilled AIEngineer 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 GenerativeAI, 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,orAWS

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.

Success Metrics

• Successful deployment of scalable AI solutions.
• Improved model accuracy, performance, and reliability.
• Reduced deployment time through MLOps automation.
• Increased business value through AI-driven insights and automation.
• High stakeholder satisfaction and adoption of AI solutions.