Lead - AI Engineer

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Experience:

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Job Summary:

We are seeking an AI Engineer with strong proficiency in Python and hands-on experience in building AI-powered applications. The ideal candidate should have experience working with FastAPI, Langchain, and Pydantic, along with a solid understanding of Generative AI concepts, Large Language Models (LLMs), Prompt Engineering, and Retrieval-Augmented Generation (RAG).

Key Responsibilities:

• Develop, integrate, and optimize AI-powered applications using FastAPI and Langchain.
• Design and deploy APIs using FastAPI with Pydantic for data validation.
• Implement and fine-tune solutions leveraging Large Language Models (LLMs).
• Build and optimize Prompt Engineering pipelines for LLM interactions.
• Design and implement Retrieval-Augmented Generation (RAG) solutions for enhanced contextual responses.
• Collaborate with data scientists, product managers, and engineers to deliver high-quality AI applications.
• Continuously research and experiment with advancements in Generative AI technologies.

Key Skills & Technologies:

• Programming:

  Python (Intermediate to Advanced)

• Frameworks & Libraries:

• FastAPI (API development)
• Langchain (LLM integrations & workflows)
• Pydantic (Data validation and settings management)

• AI/ML Concepts:

• Generative AI (Basics)
• Large Language Models (LLM) Understanding architecture, capabilities, and limitations
• Prompt Engineering – Techniques for effective LLM interactions
• Retrieval-Augmented Generation (RAG) – Building hybrid retrieval-generation systems

• Version Control:

  Git, GitHub/GitLab

• CI/CD:

  Familiarity with deployment pipelines (optional)

Preferred/Optional (Good to Have):

• Experience with AI Agent Frameworks such as:
• LangGraph
• CrewAI
• Knowledge of Vector Databases (e.g., FAISS, Chroma)
• Cloud Platforms (AWS, Azure, GCP)
• Containerization (Docker)