Job Summary

We are seeking a skilled GenAI, Agentic AI, and Data Science Engineer to design, develop, and deploy AI-driven solutions that leverage Large Language Models (LLMs), autonomous AI agents, and advanced analytics. The ideal candidate will have experience in Generative AI, machine learning, data science, and agent-based frameworks to build intelligent systems that automate business processes and deliver actionable insights.

5-8 Years of Experience

Key Responsibilities

- Design and develop Generative AI applications using LLMs such as GPT, Claude, Gemini, or open-source models.
- Build and deploy Agentic AI solutions capable of autonomous reasoning, planning, tool usage, and workflow orchestration.
- Develop RAG (Retrieval-Augmented Generation) pipelines using vector databases and enterprise knowledge sources.
- Fine-tune, evaluate, and optimize foundation models for domain-specific use cases.
- Perform data analysis, feature engineering, model development, and predictive analytics.
- Design machine learning and deep learning models for business problems.
- Integrate AI agents with APIs, databases, cloud services, and enterprise applications.
- Monitor model performance, improve prompt engineering strategies, and ensure responsible AI practices.
- Collaborate with business stakeholders, product teams, and data engineers to deliver AI solutions.
- Document technical designs, experiments, and deployment processes.

Required Skills

Generative AI

- Experience with LLMs, Prompt Engineering, Fine-Tuning, RAG, Embeddings.
- Knowledge of frameworks such as LangChain, LangGraph, LlamaIndex, CrewAI, AutoGen, or similar.

Agentic AI

- Experience building multi-agent systems and autonomous workflows.
- Understanding of planning,



memory, reasoning, tool calling, and agent orchestration.

Data Science & Machine Learning

- Solid knowledge of Machine Learning, Deep Learning, NLP, and Statistical Modeling.
- Experience with Python, Pandas, NumPy, Scikit-learn, TensorFlow, or PyTorch.
- Data visualization using Power BI, Tableau, Matplotlib, or Seaborn.

Data Engineering

- Experience with SQL, NoSQL databases, ETL pipelines, and vector databases.
- Knowledge of data processing frameworks and cloud data platforms.

Cloud & Deployment

- Experience with cloud platforms such as Amazon Web Services, Microsoft Azure, or Google Cloud.
- Familiarity with Docker, Kubernetes, CI/CD, and MLOps practices.

Preferred Qualifications
- Bachelors or Masters degree in Computer Science, Data Science, Artificial Intelligence, or related field.
- Experience with enterprise AI deployments and production-grade AI systems.
- Knowledge of AI governance, model evaluation, and responsible AI practices.
- Relevant certifications in AI/ML, cloud technologies, or data science.

Nice to Have
- Knowledge of multimodal AI (text, image, audio, video).
- Experience with graph databases and knowledge graphs.
- Exposure to reinforcement learning and advanced AI agent architectures.

Key Deliverables
- Production-ready GenAI applications.
- Agentic AI workflows and autonomous agents.
- Predictive analytics and machine learning models.
- AI-powered business automation solutions.
- Scalable and secure AI deployments.

Disclaimer: This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.

📌 Data Science or Machine Learning Engineer (India)
🏢 Sparix Global
📍 India