Role: AI Engineer (Junior)
Year: 2026
Qualification: Bachelors
Experience (years): 0-1
Job description:
• Strong understanding of RAG architecture — document chunking, embedding, retrieval, reranking, and synthesis.
• Proficiency in Python, including libraries like Pandas,Numpy, and Scikit-learn.
• Experience withFastAPIor Flask for microservice and API development.
• Hands-on withLangGraph,LangChain, or MCP for multi-agent orchestration.
• Familiarity with vector databases (FAISS,ChromaDB,Weaviate, Elasticsearch).
• Good Working knowledge of ML/DL frameworks (TensorFlow,PyTorch).
• Understanding of model serving via REST APIs, batch jobs, or pipelines.
• Exposure to containerization (Docker) and scalable architecture patterns.
• Familiarity with Git,MLflow, or DVC for versioning, tracking, and collaboration.
• Awareness of cloud AI/ML services (Azure ML, AWS SageMaker, GCP Vertex AI).
• Understanding of prompt evaluation, retrieval accuracy metrics, and contextual reasoning benchmarks.
• Curiosity to explore Agentic AI frameworks and autonomous reasoning systems.
• Analytical mindset with a focus on debugging, optimization, and scalability.
• Strong communication and documentation skills for collaborative workflows.
• Innovative and research-driven approach toward new AI architectures.
• Eagerness to experiment, iterate, and learn from production-level systems. 
Technical skills: Python, ML, RAG, APIs, LangChain, LangGraph, MCP, TensorFlow/PyTorch, Docker, Git, Github, MLflow, AWS/Azure
Soft skills: Communication, Problem Solving