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
- 3+ years of hands-on experience developing Python-based AI/ML applications.
- 9+ 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.
Skills: devops,azure ai/ml,adfs,microsoft certified application,azure ope ai,llm,ai-102,ai/ml,mlops,powerbi
