Data Scientist

About the Role

Straive is looking for a talented and driven Consultant / Data Scientist / GenAI Engineer to join our Analytics & GenAI delivery team . In this role, you will work under the guidance of the Senior Project Manager / Engagement Manager to design, develop, and deploy advanced AI/ML and Generative AI solutions for global enterprise clients. You will be part of a high-performing team, collaborating with both onshore and offshore members to build scalable, production-grade AI systems.

This role is ideal for candidates from premier engineering institutes with 2–3 years of relevant experience in Python development, LLM integration, and RAG workflows, along with a passion for solving complex problems in real-world business contexts.

Key Responsibilities

• Develop and maintain Python-based applications, AI/ML models, and data processing pipelines for GenAI projects.
• Implement Large Language Model (LLM) integrations, including Retrieval-Augmented Generation (RAG) pipelines and embedding-based search solutions.
• Build data ingestion and transformation workflows, working with structured and unstructured datasets.
• Optimize AI model performance through prompt engineering , fine-tuning, and evaluation techniques.
• Collaborate closely with senior team members to translate business requirements into technical solutions.
• Integrate AI solutions with vector databases (e.g., Cosmos DB, Pinecone, ChromaDB) and API-driven applications.
• (Optional) Contribute to cloud-native deployments and Azure architecture –based solutions, including containerization, CI/CD, and basic MLOps workflows.
• Document workflows, maintain code repositories, and follow Agile development practices.

Required Qualifications

• 2–3 years of relevant experience in AI/ML development, preferably in enterprise projects.
• Bachelor’s or Master’s degree in Computer Science, Data Science, AI/ML, or related field from a premier engineering institute .
• Proficiency in Python programming and familiarity with relevant libraries (e.g., LangChain, Hugging Face, Pandas, NumPy).
• Hands-on experience implementing RAG pipelines , embeddings, and vector search solutions.
• Understanding of LLM architectures and integration patterns.
• Working knowledge of SQL and data processing best practices.
• Basic knowledge of cloud DevOps concepts , preferably with Azure (AWS/GCP experience is also acceptable).

Preferred Skills

• Exposure to agentic AI frameworks such as LangGraph, Semantic Kernel, or similar.
• Familiarity with ML model lifecycle management and deployment workflows.
• Prior experience working with cross-border teams and Agile environments.