AI/ML Engineer

Role Overview

The AI/ML Engineer will be responsible for designing, developing, and deploying AI-powered applications and intelligent agents leveraging Large Language Models (LLMs) and agentic AI frameworks. The ideal candidate has a deep understanding of Python, machine learning frameworks, and Azure AI services, with hands-on experience in building RAG-enabled applications, LLM-based automation, and AI-driven analytics in enterprise or financial environments.

You will work collaboratively with cross-functional teams to integrate AI capabilities into business applications, ensuring scalability, reliability, and innovation.

Scope of Work

The selected candidate will:

• Develop LLM-powered applications using frameworks such as LangChain, LangGraph, MS Autogen, or similar.

• Implement Retrieval-Augmented Generation (RAG) and Model Context Protocol (MCP) to integrate LLMs with structured and unstructured data sources.

• Design and deploy AI agents capable of reasoning, planning, and executing business workflows autonomously.

• Build scalable AI/ML applications using Python and modern frameworks (TensorFlow, PyTorch, Scikit-learn).

• Leverage Azure AI/ML services, including Cognitive Services, OpenAI, and Azure Machine Learning for model training and deployment.

• Apply ML best practices for model versioning, evaluation, monitoring, and optimization.

• Collaborate with business analysts, data engineers, and solution architects to translate functional requirements into AI solutions.

• Participate in Agile/Scrum ceremonies, conduct peer reviews, and contribute to architecture discussions.

• Document technical designs, data flows, model behavior, and test cases as per enterprise standards.

• Provide technical mentorship and knowledge transfer to team members.

• Support production deployment, troubleshooting, and continuous model improvement cycles.

Required Skills Experience

• 5+ years of hands-on experience developing Python-based AI/ML applications.

• 3+ months of practical experience in agentic AI or LLM-based application development (LangChain, LangGraph, MS Autogen, or equivalent).

• Solid understanding of AI/ML concepts, NLP, model fine-tuning, and vector databases (FAISS, Pinecone, Chroma, etc.).

• Experience with Azure AI/ML, Azure OpenAI, Azure Data Factory, and Cognitive Services.

• Proficiency in data processing, cleansing, and feature engineering.

• Familiarity with DevOps pipelines, CI/CD for ML (MLOps), and version control (Git/Azure Repos).

• Strong collaboration skills and ability to communicate technical concepts to non-technical stakeholders.

• Exposure to the financial domain or compliance-driven environments is a plus.

Preferred Skills

• Knowledge of prompt engineering, function calling, and multi-agent orchestration.

• Understanding of Azure Synapse, Data Lake, and Power BI integrations.

• Hands-on experience with Docker, Kubernetes, or containerized ML deployments.

• Familiarity with LLMOps and AI observability tools (Weights Biases, MLflow, LangSmith).

• Experience in Agile/SAFe delivery models.

Certifications (Preferred but not Mandatory)

• Microsoft Certified: Azure AI Engineer Associate (AI-102)

• Microsoft Certified: Azure Data Scientist Associate (DP-100)

• Databricks Certified Machine Learning Professional

• OpenAI Developer or LangChain Certified Developer (if available)

• SAFe Practitioner or Agile Foundation Certification

Educational Qualifications

• Bachelor s or Master s degree in Computer Science, AI/ML, Data Science, or a related discipline.