Data Science Engineer

Key Skill sets

• Gen AI/Agentic AI -Python, RAG, Prompt Engg.

4- 12 yrs

P2/P3/P4

Practical exposure to Generative AI (GenAI) and DL frameworks
Strong programming skills in Python and experience with Linux/Windows environments

Proficiency with common data science toolkits:
TensorFlow, Keras, PyTorch, Pandas, NumPy, etc.
Familiarity with GenAI frameworks:
LangChain, LlamaIndex, LangGraph, CrewAI, NeMo Agent Toolkit, NAT

Hands-on experience with Cloud platforms:
Azure, AWS, or GCP
Familiarity with Git, Docker, and Kubernetes
Strong problem-solving skills.

• AI/ML, Python

4- 12 yrs

P2/P3/P4

AWS Bedrock fundamentals
AWS Neo, prompt engineering
Strong Python fundamentals
REST APIs and integration patterns
Basic understanding of multi agent workflows

25 years in Python / AI / backend development
Exposure to cloud-native development preferred

• MLOps Engineer

4- 12 yrs

P2/P3/P4

Strong Python and SQL skills.
Experience with ML platforms such as Databricks, MLflow, SageMaker.
Knowledge of CI/CD tools and DevOps practices.

Experience with cloud platforms (AWS, Azure, or GCP).
Understanding of model lifecycle management and monitoring concepts.
Familiarity with containerization and orchestration (Docker, Kubernetes) is a plus.
Preferred Experience

• MS Copilot, power platform and copilot studio

4- 12 yrs

P2/P3/P4

Primary Skills - Microsoft Power Platform Canvas Model Driven Dataverse CoPilot Studio

Minimum 1 year CoPilot experience

Deep understanding of Microsoft Azure Power Platform Microsoft 365 and Copilot extensibility

Experience in developing custom web resources for PowerApps