About this role
Summary: Design, develop, and deploy scalable AI solutions including RAG, Generative AI, and Computer Vision. Collaborate with stakeholders to translate business challenges into technical implementations using Python, Azure, and MLOps practices.
Job Overview
The Advanced Analytics & AI team is seeking an AI Engineer to design, develop, deploy, and maintain scalable, secure AI solutions.
The role involves working closely with business stakeholders across Operations, Logistics, Quality, Sales, and other functions to translate business challenges into practical AI solutions
Responsibilities
- Work closely with business stakeholders to understand requirements and translate them into technical solutions.
- Design and develop scalable AI solutions including RAG, AI Agents, Generative AI, ML, Computer Vision, and multimodal applications.
- Develop Python applications, APIs, data pipelines, and AI/ML solutions.
- Perform EDA, data validation, cleansing, transformation, and quality checks.
- Develop statistical, predictive, machine-learning, and anomaly-detection models.
- Integrate and optimize AI models, LLMs, APIs, cloud AI services, and enterprise data platforms.
- Create dashboards, reports, and visualizations using Power BI and Qlik.
- Implement MLOps practices, including CI/CD, versioning, deployment, monitoring, logging, and alerting.
- Ensure solutions meet enterprise standards for architecture, security, governance, scalability, reliability, and performance.
- Support UAT, troubleshooting and continuous improvement.
- Handing over to solution delivery team for production and monitoring
- Document solution architecture, technical designs, data flows, experiments, and implementation approaches.
- Stay updated with emerging AI technologies and relevant business-domain knowledge.
Main Competence Requirements
- Programming: Strong hands-on experience with Python and API development.
- AI/ML: Strong knowledge of Machine Learning, Generative AI, LLMs, RAG, AI Agents, prompt engineering, and Computer Vision.
- Cloud: Hands-on experience with Microsoft Azure and relevant AI/data services.
- Data & Analytics: Experience with SQL, EDA, statistical modelling, predictive analytics, and structured/unstructured data.
- Visualization: Experience with Power BI and/or Qlik.
- MLOps/DevOps: Understanding of CI/CD, model versioning, deployment automation, monitoring, and logging.
- Solution Architecture: Ability to design scalable, secure, reliable, and maintainable AI solutions.
- Problem Solving: Ability to translate complex business problems into practical technical solutions.
- Communication & Collaboration: Strong stakeholder communication and ability to work with cross-functional teams.
- Ownership: Result-oriented mindset with accountability and continuous improvement.
- Knowledge of automotive, manufacturing, logistics, quality, or sales-related business processes is an advantage.
- Relevant Microsoft Azure/AI certifications, such as AI-900, are an advantage.
Minimum Qualifications
- BE / B.Tech / MCA / M.Tech or equivalent educational qualification.
- 2–12 years of relevant professional experience in AI/ML, Advanced Analytics, Data Science, Software Development, or related areas.