Job Overview

Infineon is hiring a GenAI Data Scientist for Digital Marketing in Bangalore as part of its Advanced Analytics & Artificial Intelligence organization. This permanent professional role is designed for an experienced data science, analytics, or AI specialist who can combine hands-on data analysis with Generative AI application development.

You will create practical digital solutions that support business growth, customer experience, and operational efficiency. The work spans modern AI technologies, enterprise data platforms, dashboards, Retrieval Augmented Generation (RAG), agentic workflows, and LLM-based applications. The role also includes technical ownership, mentoring, stakeholder collaboration, and continuous improvement of solutions after deployment.

Key Responsibilities

• Design and develop Generative AI applications using foundation models and LLM services for Digital Marketing use cases.
• Build RAG systems, agentic workflows, and other AI applications that address practical business requirements.
• Apply data science and analytics techniques to identify opportunities and generate actionable insights.
• Develop end-to-end digital solutions that can include data pipelines, dashboards, AI applications, and supporting data services.
• Provide technical leadership for GenAI implementations and mentor junior engineers on LLM development, prompt engineering, and AI deployment practices.
• Own solutions from requirements gathering and design through development, deployment, improvement, and ongoing support.
• Lead digitalization and GenAI projects while coordinating dependencies across technical and business teams.
• Work with stakeholders to define requirements, communicate progress, manage expectations, and explain AI capabilities and data insights.
• Improve solution performance, accuracy, reliability, and user experience based on feedback and evolving requirements.
• Identify opportunities where AI, analytics, and digital technologies can solve business problems and create measurable value.
• Support adoption of internal digital and AI solutions by focusing on usability and business outcomes.
• Collaborate with central departments, analytics teams, and business stakeholders across the organization.

Required Skills

Strong Python programming skills are essential for data analysis and AI development. Candidates should have practical experience building AI or data science solutions and understand how modern Generative AI applications are designed and deployed.

Experience with GenAI frameworks such as LangChain or LlamaIndex and foundation models such as GPT, Claude, or LLaMA is highly relevant. Knowledge of vector databases, embedding models, semantic search, and RAG architectures is important for building enterprise AI applications.

Candidates should be proficient in SQL and comfortable working with relational and distributed data stores. Experience with MySQL or HDFS is useful. Knowledge of data orchestration tools such as Apache Airflow or Mage AI is also valuable.

A working understanding of DevOps and MLOps practices is expected, including source control, CI/CD, application automation, containerization, and orchestration. Experience with Git, Jenkins, Docker, and Kubernetes will strengthen an application.

Preferred Skills

Experience in digital marketing or sales analytics is an advantage because the position supports Digital Marketing initiatives. Additional programming experience with Java, Scala, or Rust is also useful.

Experience with Scrum, JIRA, and Confluence can help candidates work effectively within agile project environments. Exposure to enterprise AI pilots, production GenAI applications, customer-facing analytics, or technical solution ownership is particularly relevant.

Education

A degree in Information Technology, Computer Science, Data Science, Economics, Engineering, or a related field is required. The position combines AI engineering, data science, analytics, software development, and business problem-solving.

Experience

The role requires 5 or more years of relevant experience in data science, analytics, or AI roles. Candidates should have experience owning technical solutions and ideally have worked with business stakeholders or customers.

Strong applicants will be able to demonstrate experience taking solutions from requirements and design through implementation and deployment, followed by optimization and sustained use. Experience with Generative AI, digital analytics, enterprise data platforms, or AI application development is highly relevant.

Required Technologies

• Python
• Generative AI
• Large Language Models (LLMs)
• LangChain
• LlamaIndex
• GPT
• Claude
• LLaMA
• SQL
• MySQL
• HDFS
• Vector Databases
• Embedding Models
• Semantic Search
• Retrieval Augmented Generation (RAG)
• Agentic AI Workflows
• Apache Airflow
• Mage AI
• Git
• CI/CD
• Jenkins
• Docker
• Kubernetes
• Scrum
• JIRA
• Confluence

Additional programming languages mentioned as advantageous include Java, Scala, and Rust.

Soft Skills

Strong communication and stakeholder management skills are important. You should be able to explain complex AI and data concepts clearly to both technical and non-technical audiences and communicate project progress, risks, results, and limitations effectively.

Analytical thinking is important when identifying business problems and evaluating technology solutions. The role also requires curiosity about emerging technologies, an entrepreneurial mindset, attention to detail, strong organization, and the ability to manage multiple priorities.

Candidates should be comfortable collaborating across teams and organizational levels. The ability to build productive relationships with stakeholders from different professional and cultural backgrounds is valuable.

Benefits of Working in this Role

This role provides practical exposure to Generative AI, advanced analytics, enterprise data, RAG applications, agentic workflows, and modern AI engineering practices. It also combines technical delivery with business-facing solution ownership.

The position can strengthen experience in end-to-end AI solution development, production deployment, MLOps, technical leadership, stakeholder management, and digital transformation. Mentoring junior engineers and leading cross-functional initiatives can further develop leadership capabilities.

The supplied job description does not specify salary, bonus, insurance, or other individual employee benefits, so those details should not be assumed.

Work Mode

The supplied job description identifies the role as being based at Bangalore BTP but does not explicitly state whether the work arrangement is onsite, hybrid, or remote. Candidates should confirm the applicable work model with Infineon during the hiring process.

Location

The position is based at Bangalore BTP in Bangalore, Karnataka, India. It belongs to Infineon's Advanced Analytics & Artificial Intelligence organization and supports digitalization initiatives for the Power & Sensor Systems division.

The job description also states that occasional travel to Austria and Germany may be required.

Who Should Apply

This opportunity is suited to experienced Data Scientists, AI Engineers, Machine Learning professionals, Analytics Engineers, and Generative AI specialists with at least 5 years of relevant experience.

Candidates should have strong Python and SQL skills and practical exposure to AI application development. Professionals who have built RAG applications, LLM-based solutions, agentic workflows, vector search systems, or enterprise analytics platforms may be particularly well aligned.

Applicants with digital marketing analytics experience, customer-facing responsibilities, technical solution ownership, or experience leading AI pilots should highlight these areas clearly in their resumes.

Career Growth

The role can support progression toward senior data science, AI engineering, Generative AI architecture, solution architecture, technical leadership, and digital transformation positions. Experience owning enterprise AI solutions can strengthen capabilities in production AI delivery, MLOps, stakeholder management, and business-focused technology strategy.

Mentoring junior engineers and leading cross-functional initiatives also provide opportunities to develop technical leadership and project ownership skills.

Application Advice

Highlight measurable examples of AI or analytics solutions you have delivered. Mention experience with Python, SQL, LLMs, RAG, vector databases, semantic search, GenAI frameworks, enterprise data platforms, and MLOps practices where applicable.

Describe the lifecycle of important projects, including requirements, architecture, development, deployment, monitoring, and optimization. If you have worked in digital marketing or sales analytics, explain how your solutions improved decision-making, customer experience, operational efficiency, or another measurable business outcome.

Also emphasize experience communicating with senior stakeholders, mentoring engineers, managing project dependencies, and translating complex AI concepts into practical business solutions.