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:
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