AI Engineer

AI Engineer

Key Responsibilities:

• Design, develop, and deploy

  Generative AI solutions

  using

  LLMs and NLP techniques

• Implement

  Retrieval-Augmented Generation (RAG)

  pipelines for intelligent search and knowledge systems
• Work extensively with

  OpenAI APIs

  and

  LangChain

  frameworks
• Build and manage data pipelines using

  Vector Databases

  and

  Graph Databases

• Apply traditional

  Machine Learning algorithms

  for predictive and analytical use cases
• Collaborate with cross-functional teams to translate business requirements into AI-driven solutions
  
• Optimize model performance, scalability, and reliability in production environments
  

Technical Skills & Requirements:

• Strong understanding of

  LLMs, NLP, and Generative AI concepts

• Hands-on experience with

  OpenAI

  ,

  LangChain

  , and

  RAG architectures

• Experience with

  Graph Databases

  such as

  Neo4j, ArangoDB

• Experience with

  Vector Databases

  such as

  Pinecone, Weaviate

• Proven track record of delivering

  Generative AI projects

  (references or examples preferred)
• Solid knowledge of

  traditional ML algorithms

  and their real-world applications
• Hands-on experience with

  scikit-learn, TensorFlow, or PyTorch

• Proficiency in

  Python

  with strong data handling skills using

  Pandas and NumPy

• Experience with

  data visualization tools

  like

  Matplotlib or Seaborn

• Familiarity with

  relational databases

  (PostgreSQL, SQL Server) and

  NoSQL databases

  (MongoDB, Redis)

Preferred Skills:

• Experience deploying AI models in

  production environments

• Knowledge of

  cloud platforms

  (AWS, Azure, or GCP)
• Understanding of

  MLOps

  practices and model lifecycle management