Senior AI Engineer / Data Scientist (Agentic AI)

Job Description

Senior AI Engineer / Data Scientist (Agentic AI)

Experience: 8+ Years
Location: Office
Employment Type: Full-Time / Consultant

Role Overview

We are seeking a highly skilled Senior AI Engineer / Data Scientist with 8+ years of experience in building enterprise-scale AI, Machine Learning, Data Science, and Generative AI solutions. The ideal candidate should possess strong expertise in designing and implementing Agentic AI systems, multi-agent architectures, LLM orchestration frameworks, RAG pipelines, and AI-driven automation solutions.

This role requires a mix of Data Science, AI Engineering, MLOps, Cloud Engineering, and Software Development skills to develop next-generation autonomous AI platforms that deliver measurable business outcomes.

Key Responsibilities

Agentic AI & Generative AI

• Design and develop Agentic AI solutions using autonomous and multi-agent frameworks.
  
• Build AI agents capable of reasoning, planning, tool usage, memory management, and workflow orchestration.
  
• Implement multi-agent systems for enterprise workflows, analytics, customer service, and decision intelligence.
  
• Develop AI copilots, virtual assistants, and autonomous business agents.
  
• Design AI orchestration architectures using:
  
• LangGraph
  
• LangChain
  
• AutoGen
  
• CrewAI
  
• OpenAI Agent Framework
  
• Microsoft Copilot Studio
  

Large Language Models (LLMs)

• Fine-tune and optimize LLMs for enterprise use cases.
  
• Implement prompt engineering, prompt tuning, and evaluation frameworks.
  
• Develop RAG (Retrieval Augmented Generation) architectures.
  
• Build semantic search and knowledge retrieval solutions.
  
• Integrate vector databases such as:
  
• Azure AI Search
  
• Milvus
  

Data Science & Machine Learning

• Develop predictive and prescriptive analytics models.
  
• Build recommendation systems and forecasting solutions.
  
• Apply advanced statistical analysis and machine learning techniques.
  
• Design feature engineering pipelines and model optimization strategies.
  
• Build and deploy models using:
  
• Scikit-Learn
  
• XGBoost
  
• TensorFlow
  
• PyTorch
  
• Hugging Face
  

AI Engineering Responsibilities

• Develop scalable AI services and APIs.
  
• Build enterprise-grade AI microservices.
  
• Create reusable AI accelerators and frameworks.
  
• Design AI governance and observability frameworks.
  
• Implement AI monitoring and model performance tracking.
  
• Develop AI safety, guardrails, and responsible AI controls.
  

Cloud & Platform Engineering

Azure (Preferred)

• Azure OpenAI
  
• Azure AI Search
  
• Azure Machine Learning
  

Other Cloud Platforms

• AWS Bedrock
  
• Amazon SageMaker
  
• Google Vertex AI
  

Software Development Skills

Strong hands-on programming expertise in:

• Python (Mandatory)
  
• SQL
  
• REST APIs
  
• GraphQL
  

Experience with:

• FastAPI
  
• Microservices Architecture
  
• Event-Driven Architecture
  

Required Qualifications

Education

• Bachelor's or Master's degree in:
  
• Computer Science
  
• Data Science
  
• Artificial Intelligence
  
• Machine Learning
  
• Engineering
  
• Related Discipline
  

Experience

• 8+ years in Data Science, Machine Learning, AI Engineering, or Software Engineering.
  
• 3+ years of hands-on experience with Generative AI and LLMs.
  
• 2+ years of hands-on experience implementing Agentic AI solutions.
  
• Experience delivering enterprise-scale AI platforms.
  

Required Technical Skills

Must Have

✅ Agentic AI Frameworks
✅ Generative AI & LLMs
✅ RAG Architecture
✅ Vector Databases
✅ Python Development
✅ Machine Learning & Data Science
✅ Azure AI Services
✅ MLOps & CI/CD
✅ REST APIs
✅ Cloud Architecture

Good to Have

✅ Semantic Kernel
✅ Microsoft Fabric
✅ Databricks
✅ Knowledge Graphs
✅ GraphRAG
✅ Multi-Agent Systems
✅ AI Governance Frameworks
✅ Copilot Studio

Preferred Certifications

• Microsoft Certified: Azure AI Engineer Associate
  
• Microsoft Certified: Azure Data Scientist Associate
  
• Databricks Certified Data Engineer
  
• AWS Machine Learning Specialty
  
• Generative AI Certifications (Microsoft/OpenAI)
  

Success Metrics

• Successful deployment of enterprise AI agents.
  
• Reduction in manual effort through AI automation.
  
• Increased model accuracy and business adoption.
  
• AI platform scalability, performance, and governance compliance.
  
• Delivery of measurable business value from Agentic AI initiatives.
  

Target Titles

• Senior AI Engineer
  
• Lead AI Engineer
  
• Staff AI Engineer
  
• Principal AI Engineer
  
• Senior Data Scientist (Agentic AI)
  
• AI Solutions Architect