Key Responsibilities :

- Architect, develop, and deploy end-to-end LLM-based solutions and Generative AI applications.

- Design and implement Retrieval-Augmented Generation (RAG) systems, agentic AI workflows, and document automation pipelines.

- Develop and integrate multimodal AI capabilities across relevant business applications.

- Implement LLMOps practices, including prompt engineering, model orchestration, evaluation frameworks, and structured output generation.

- Establish evaluation methodologies to assess model accuracy, reliability, and response quality.

- Build scalable backend services and APIs using Python, FastAPI/Django, and TypeScript.

- Integrate AI solutions with enterprise applications using RESTful APIs and SQL-based systems.

- Deploy and manage containerised applications using Docker and Azure cloud services.

- Optimise AI solutions for performance, scalability, reliability, and production readiness.

- Collaborate with cross-functional teams to ensure seamless integration and delivery of AI solutions.

- Work across machine learning, NLP, computer vision, statistical modelling, and data-processing pipelines.

Required Candidate Profile :

- 3 - 4 years of experience working in a corporate environment.

- Proven experience architecting and deploying LLM-based solutions and Generative AI applications.

- Strong understanding of RAG architectures, agentic AI frameworks, document automation, and multimodal AI.

- Hands-on expertise in LLMOps, including:

- Prompt engineering and optimisation

- Model evaluation methodologies

- Model orchestration

- Structured and standardised output generation

- Production deployment and monitoring

- Strong full-stack engineering experience with Python and TypeScript.

- Experience with FastAPI or Django, RESTful API development, and SQL.

- Understanding of cloud-native architectures, preferably on Microsoft Azure.

- Hands-on experience with Docker and Azure services.

- Knowledge of machine learning, NLP, computer vision, and statistical modelling.

- Experience with data-processing pipelines and data visualisation tools such as Power BI.

Preferred Skills :

- Experience building production-grade enterprise AI applications.

- Knowledge of LLM evaluation, reliability optimisation, and model performance tuning.

- Experience integrating AI solutions into existing enterprise systems.

- Strong collaboration, communication, and problem-solving skills.

Allianz People Attributes :

- Customer & Market Excellence

- Collaborative Leadership

- Entrepreneurship

- Trust

- Learning & Development

- Allianz supports continuous learning and professional development through resources such as LinkedIn Learning and other learning opportunities.

Key Skills:

- Generative AI, LLMs, LLMOps, RAG, Agentic AI, Prompt Engineering, Model Orchestration, LLM Evaluation, Multimodal AI, Document Automation, Python, TypeScript, FastAPI, Django, REST APIs, SQL, Azure, Docker, Machine Learning, NLP, Computer Vision, Statistical Modelling, Power BI