AI Engineer

**TECHNICAL SKILLS: minimum 3-4 yrs of working experience mandatory

Azure AI Services:** Demonstrated working experience with Microsoft Azure AI Services including Azure OpenAI, Azure Machine Learning, Azure Cognitive Services, Azure AI Search, Azure Functions, and Azure Databricks.

Python Programming: Strong proficiency in Python programming, including experience with REST APIs, SDKs, asynchronous processing, data manipulation, backend development, and AI application frameworks (LangChain, LlamaIndex, Semantic Kernel, LangGraph, FastAPI).

LLM & Generative AI: Deep understanding of machine learning, statistical modeling, NLP, generative AI principles, LLM application development, prompt engineering, RAG architecture, embeddings, vector databases, semantic search, and model evaluation techniques.

ML Libraries & Frameworks: Advanced proficiency in ML libraries such as PyTorch, TensorFlow, Hugging Face Transformers, scikit-learn, and NLP libraries (spaCy, NLTK).

Vector Databases: Experience with vector databases including FAISS, Azure AI Search, ChromaDB, and Pinecone.

DevOps/MLOps: Hands-on experience with DevOps/MLOps practices and tools such as Git, Docker, Kubernetes, CI/CD pipelines, MLflow, Terraform, Azure Monitor, and Application Insights.

Cloud Security & Integration: Understanding of cloud security, identity and access management, data privacy, encryption, logging, monitoring, and secure API integration patterns.

AI Ethics & Governance: Awareness of ethical considerations and responsible AI practices, including fairness, accountability, transparency, bias detection, hallucination mitigation, and compliance in AI systems.

**KNOWLEDGE, SKILLS, & EXPERIENCE

Minimum Qualifications:**

Bachelor's degree in Computer Science, Engineering, Artificial Intelligence, Data Science, Mathematics, Statistics, or related field; Master's degree is preferred. Microsoft Certified: Azure AI Engineer Associate (AI-102) certification is highly preferred.

Minimum Experience:

3+ years of hands-on experience in designing, developing, and deploying AI/ML or Generative AI solutions in production environments.

Mandatory hands-on experience with Microsoft Azure AI Services.

Experience working with large-scale datasets and real-time enterprise data.

Experience in financial services, banking, risk, compliance, customer service, or regulated enterprise environments is an advantage.