Data Scientist

Essential functions

Design, develop, and maintain GenAI applications and agentic workflows using Python, Go, and Node.js.

Implement Retrieval-Augmented Generation (RAG) pipelines with vector stores and embeddings.

Integrate LLM agents (LangChain, CrewAI, Aider, Cline) into enterprise workflows.

Develop APIs using Flask or Fast API for scalable microservices.

Ensure coding standards, CI/CD pipelines, and deployment automation using Git, Jenkins, and container orchestration.

Manage Docker, Kubernetes, and Linux-based environments for cloud-native deployments.

Work with Azure, AWS, and hybrid cloud setups for GenAI workloads.

Collaborate on fine-tuning models, prompt engineering, and multi-provider AI integration (OpenAI, Anthropic, Gemini).

Optimize performance and security for enterprise-grade AI solutions.

Qualifications

Programming Languages: Python (Flask/Fast API), Go, Node.js.

Foundational Knowledge: Data Structures & Algorithms, coding best practices.

DevOps: Git, Jenkins, CI/CD, Docker, Kubernetes.

Cloud Platforms: Azure, AWS.

GenAI Expertise: RAG pipelines, embeddings, vector stores, LangChain/CrewAI.

Model Ecosystem: OpenAI GPT, Anthropic Claude, Google Gemini.

Linux Systems: Shell scripting and container management.

Experience with multi-modal AI, agentic frameworks, and cloud-native architectures.

Strong experience in building and deploying Agentic RAG and Worked extensively on MCP

Would be a plus

Linux Systems Shell scripting, container orchestration Intermediate

We offer

• Opportunity to work on bleeding-edge projects
• Work with a highly motivated and dedicated team
• Competitive salary
• Flexible schedule
• Benefits package - medical insurance, sports
• Corporate social events
• Professional development opportunities
• Well-equipped office