Artificial Intelligence Engineer

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Department:

Job Summary

AI Engineer

Key Responsibilities

Area

Responsibility

AI/ML Development

Design, train, and fine-tune ML models including NLP, recommendation systems, predictive analytics.

LLM & Generative AI

Integrate and optimize LLMs (e.g., OpenAI, Azure OpenAI, Claude, Gemini) into enterprise use cases.

Agentic AI Systems

Build autonomous AI agents with memory, reasoning, and workflow execution capabilities.

Data Lake Integration

Collaborate with Data Engineers to ingest and prepare data from Data Lake/Fabric.

MLOps & Deployment

Package and deploy models using containers (Docker, Kubernetes) and CI/CD pipelines.

Data Governance

Ensure all models use compliant, secure, and auditable data pipelines.

Performance Monitoring

Set up model monitoring, drift detection, and continuous improvement loops.

Collaboration

Work cross-functionally with product, data, and engineering teams.

Required Skills and Experience

• 3–6 years of experience in AI/ML development or applied data science.
• Strong experience with

  Python

  , PyTorch/TensorFlow, LongChain, HuggingFace, Scikit-learn.
• Experience working with

  LLMs

  , vector databases (e.g., Pinecone, Weaviate, FAISS), and embeddings.
• Good understanding of

  Azure ML

  ,

  Azure Fabric

  , or other cloud-based AI services.
• Proficiency in REST APIs, JSON, and integrating AI into applications via microservices.
• Familiarity with tools like

  Fivetran

  ,

  Power BI

  ,

  dbt

  , or

  Data Factory

  is a plus.
• Experience with

  MLOps

  tools like MLflow, Weights & Biases, or Azure DevOps.
• Knowledge of

  data governance

  , privacy, responsible AI principles, AI-driven security and predictive analytics.

Preferred Qualifications

• Degree in Computer Science, AI, Data Science, or related field.
• Experience in building enterprise-grade AI copilots or chatbots.
• Knowledge of business domains like eCommerce, Supply Chain, or Retail.
• Certification in Azure AI Engineer or equivalent is a plus.

Soft Skills

• Strong problem-solving and analytical thinking.
• Excellent communication and documentation skills.
• Entrepreneurial mindset with ability to work in fast-paced environments.
• Ownership-driven and collaborative.

Opportunities

• Work on high-impact AI products with real-world business applications.
• Exposure to enterprise architecture, data platforms, and full AI lifecycle.
• Be part of a team shaping the future of GenAI and Agentic AI.