Agentic AI Engineer

Key Responsibilities:

• Design and Implement RAG-Based Solutions:

  Lead the development of a robust RAG-based system that seamlessly integrates generative AI models with retrieval mechanisms, ensuring optimal accuracy, performance, and scalability.

• Agent-Based Solution Development

  : Build AI agents that can autonomously perform tasks using information retrieval, language models, and multi-turn interactions using AutoGen, LangGraph frameworks.

• Generative AI Integration

  : Leveraging

  LLMs

  (e.g., GPT, Anthropic, Llama, Deepseek etc.) for generating high-quality, contextually accurate content in response to user queries.

• Prompt Engineering:

  Strong proficiency in prompt engineering to design, test, and optimize prompts for large language models, ensuring effective agent behavior and task completion

• Data & Knowledge Integration

  : Work on integrating structured and unstructured data sources into the RAG framework to improve model outputs.

• Collaborate with Teams

  : Work closely with product, engineering, and data science teams to ensure seamless integration of AI capabilities into broader products.

• Security & Compliance

  : Ensure following best practices in data security, privacy, and compliance, particularly in AI-driven applications.

• Model Evaluation

  : Implement strategies for continuous evaluation, monitoring, and tuning of models to ensure high-quality outputs.

• Data Pipeline Design

  : Build robust

  data pipelines

  for preprocessing and integrating structured and unstructured data sources into the platform.

• Collaborate with Teams

  : Work closely with data engineers, and software engineers to ensure seamless integration of machine learning models into production environments.

• Performance Optimization

  : Implement and experiment with various techniques such as

  vector search

  ,

  semantic search

  , and

  knowledge distillation

  to enhance the platforms efficiency and accuracy.

• Data Quality

  : Ensure data quality and consistency throughout the data pipeline, implementing necessary quality checks and validation processes.

Requirements:

• 4+ years of experience with building GenAI solutions using Python and Langchain and AutoGen technologies.
• Agentic AI experienced developing agents using AutoGen and LangGraph frameworks.
• Prior experience in building GenAI solutions using effective text representation techniques and classification algorithms.
• Experience with ML – Model Building, Semantic extraction techniques, data structures and modelling
• Experience with Supervised/Unsupervised Learning, Sentiment Analysis, Statistical Analysis using NLP and Python libraries (NLTK, Spacy, Numpy, Pandas)
• Experienced in building Rest API’s
• Experience with building applications with micro services & serverless architecture
• Excellent communication skills

Good to have:

• Experience with Azure cloud services
• Experience with Azure Foundry & Prompt flow