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

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

Good to
Have

âœ
Semantic Kernel
âœ
Microsoft Fabric
âœ
Databricks
âœ
Knowledge Graphs
âœ
GraphRAG
âœ
Multi-Agent Systems
âœ
AI Governance Frameworks
âœ
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