Job Title

About the Role Straive is looking for a talented and drivenConsultant / Data Scientist / GenAI Engineerto join ourAnalytics & 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 frompremier engineering instituteswith2–3 years of relevant experiencein Python development, LLM integration, and RAG workflows, along with a passion for solving complex problems in real-world business contexts.Key Responsibilities Develop and maintainPython-basedapplications, AI/ML models, and data processing pipelines for GenAI projects. ImplementLarge Language Model (LLM)integrations, includingRetrieval-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 throughprompt engineering , fine-tuning, and evaluation techniques. Collaborate closely with senior team members to translate business requirements into technical solutions. Integrate AI solutions withvector databases(e.g., Cosmos DB, Pinecone, ChromaDB) and API-driven applications. (Optional) Contribute tocloud-native deploymentsandAzure 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 yearsof 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 apremier engineering institute . Proficiency inPythonprogramming and familiarity with relevant libraries (e.g., LangChain, Hugging Face, Pandas, NumPy). Hands-on experience implementingRAG pipelines , embeddings, and vector search solutions. Understanding ofLLM architecturesand integration patterns. Working knowledge ofSQLand data processing best practices. Basic knowledge ofcloud DevOps concepts , preferably withAzure(AWS/GCP experience is also acceptable).Preferred Skills Exposure toagentic AI frameworkssuch 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.