AI & Data Engineer

cgi

Bangalore 6 Years Exp Posted 7h ago

Job Description

We are looking for a highly skilled AI & Data Engineer (L3) who can design, build, and deploy scalable data pipelines and AI/ML solutions. The ideal candidate will have strong experience in data engineering, machine learning, and cloud platforms, with the ability to translate business requirements into robust, production-grade AI solutions.
Key Responsibilities:
 
Data Engineering & Pipeline Development:
- Design, build, and optimize ETL/ELT pipelines using tools like Azure Data Factory,     Databricks,     or Spark
- Develop and manage data ingestion frameworks for structured and unstructured data
- Ensure data quality, governance, and reliability across pipelines
AI / ML Solution Development:
- Build, train, and deploy machine learning and AI models
- Work with Generative AI (LLMs, RAG, prompt engineering)
- Perform data preprocessing, feature engineering, and model evaluation
MLOps & Deployment:
- Deploy models using CI/CD pipelines and MLOps practices
- Work with MLflow, Docker, Kubernetes, Azure ML
- Develop REST APIs to expose ML models
Cloud & Platform Engineering:
- Work on Azure/AWS/GCP platforms
- Optimize performance and cost
Collaboration & Delivery:
- Collaborate with cross-functional teams
- Translate business requirements into technical solutions
- Participate in Agile ceremonies
Primary Skills:
- Python, SQL
- Azure Data Factory / Databricks / Spark
- Scikit-learn / TensorFlow / PyTorch
- Pandas, NumPy
- Azure/AWS/GCP
- MLflow, CI/CD
- REST APIs
- SQL/NoSQL databases
Secondary Skills:
- LLMs, LangChain, RAG
- Kafka, Delta Lake
- Power BI/Tableau
- Docker, Kubernetes
- GitHub Actions / Azure DevOps
Qualifications:
- Bachelor's or Master's degree in relevant field
Experience Requirements:
- 5–8 years experience
- 3+ years in Data Engineering / AI/ML roles
- Agile experience
Soft Skills:
- Strong problem-solving
- Good communication
- Team collaboration
Ideal Candidate Profile:
- Strong hands-on engineer
- Experience in data pipelines and ML deployment
- Ability to bridge data engineering and AI