Fullstack Data Engineer - Applied & Agentic AI Systems

Job description

Description of the area

Job Responsibilities

• Generative AI Application Co-creation : Collaborate with AI engineers, data scientists, product owners, and other developers in Agile teams to integrate LLMs into scalable, robust, fair, and ethical end-user applications, focusing on user experience, relevance, and real-time performance
• Data Infrastructure Development and Data Integration : Design and implement scalable, high-performance data pipelines for AI/GenAI applications, ensuring efficient data ingestion, transformation, storage and retrieval; integrate different databases, requiring understanding of data architectures / Domain data ecosystem
• Vector Databases : work with vector databases (e.g., AWS OpenSearch, Azure AI Search) to facilitate scalable, high-speed similarity search and RAG for generative AI applications with high-dimensional data.
• Graph Databases : Work with graph databases (e.g., Neo4j, AWS Neptune) to enable GraphRAG, support multi-hop logical reasoning for agentic workflows, and provide auditable explainability for enterprise AI decision-making.
• Cloud-Based Data Engineering: Build and maintain cloud-based data solutions using AWS (OpenSearch, S3) or Azure (Azure AI Search, Azure Blob Storage)
• Snowflake Implementation: Design and optimize data storage and processing using Snowflake for scalable, cloud-native analytics solutions
• Data Processing & Transformation : Develop ETL/ELT pipelines to enable real-time and batch data processing
• Support AI Model Workflows : Collaborate with AI/ML Engineers and Data Scientists to ensure seamless integration of data pipelines with AI finetuning, inference and training workflows
• Performance Optimization : Optimize data storage, retrieval, and processing strategies for efficiency, scalability, and cost-effectiveness
• Software Development Lifecycle : understand and leverage an agentic software development lifecycle (SDLC) in day to day work
• Security & Compliance : Implement data governance, security best practices, and compliance measures aligned with Roche’s standards
• Monitoring & Maintenance : Set up monitoring, alerting, and logging for data pipelines, ensuring high availability and reliability

Must have

• Experience : 7+ years in data engineering, preferably supporting AI/ML applications
• Advanced Programming & SQL: Writing production-grade code in Python alongside highly optimized, complex SQL queries.
• Advanced System Architecture & Modeling: Designing scalable, fault-tolerant ETL/ELT data pipelines and Lakehouse architectures (e.g., Snowflake).
• Orchestration: Hands-on expertise with orchestration tools (like Airflow).
• Data Engineering in AI: Developing Retrieval-Augmented Generation (RAG), AI systems powered by Vector Databases and/or LLM fine-tuning, and data preparation
• Document Processing Proficiency : Extracting, transforming, and loading data from diverse file formats (PDF, DOCX, CSV, JSON, etc.), including automated parsing and information retrieval from unstructured and semi-structured documents
• Version Control & DevOps : Hands-on experience with Git, CI/CD, containerization (Docker, Kubernetes), and Infrastructure as Code (Terraform, CloudFormation)
• Problem Solving: Excellent analytical skills and the ability to tackle complex challenges with innovative solutions

Should have

Could have

Capabilities

Qualifications

• hold B.Sc., B.Eng., or higher, or equivalent in Computer Science, Data Engineering or related fields
• have an interest in AI and stay up to date with the latest advancements in data engineering
• be team-oriented, proactive, and collaborative
• have strong analytical and problem-solving skills
• have excellent verbal and written communication skills
• be detail-oriented and highly organized
• be willing to learn and expand their skill set
• have the ability to work collaboratively in a fast-paced, dynamic environment
• be able to communicate in English at the level of C1+
• Located in Hyderabad, India, with working hours structured to capture the 'golden hours' of overlap with Central European Time (typically running through the IST evening).
• #Hyd2026

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