REF97957J- Azure Data Engineering / AI Models
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Job Description
About the Role
We are seeking an experienced Senior Product & Application Engineer to join our team. The ideal candidate will have a strong background in building and shipping end-to-end data-driven and AI-powered applications from backend engineering and data pipelines through to integrating AI models, user-facing features and production deployment.
Key Responsibilities
• Design, build and ship production-grade data and AI-powered applications — owning the full stack from data ingestion and AI model integration through to application logic and user-facing interfaces.
• Develop scalable backend services and APIs to power data quality, validation, analytics and AI model serving features accessible to business users.
• Build and maintain automated data pipelines for ingestion, transformation, quality validation and delivery of structured datasets.
• Implement application features including data quality dashboards, self-serve insights, automated flagging and summary reporting at varying levels of granularity.
• Ensure robust data governance within the application audit trails, access control, lineage tracking and reproducible workflows.
• Collaborate with cross-functional teams’ analysts, data scientists and business stakeholders to translate requirements into product features.
• Support deployment and integration of the application on enterprise or client infrastructure.
• Integrate, evaluate and deploy AI/ML models into production applications — including LLM-based workflows, embedding pipelines and prompt engineering — ensuring reliability and performance at scale.
Qualifications
• 5+ years of proven experience in product or application engineering, with a track record of shipping production software not just prototyping.
• Strong proficiency in Python and backend application development; experience with REST APIs, application frameworks, and AI/ML libraries such as LangChain, OpenAI SDK, or HuggingFace Transformers.
• Solid understanding of data engineering fundamentals pipelines, transformations, schema validation and data quality.
• Experience building user-facing data and AI-powered products consumed by non-technical business users, with a focus on making AI capabilities accessible and actionable.
• Familiarity with SQL and working with structured, multi-source datasets.
• Strong problem-solving skills with the ability to work across the full application stack.
• Excellent communication skills, with the ability to explain technical decisions clearly to non-technical stakeholders.
• Ability to work independently and take end-to-end ownership in a fast-paced, product-driven environment.
• Experience with cloud deployment on Azure, AWS or GCP is a strong plus including containerisation, environment setup, managed services and deploying AI/ML model endpoints in production.
Requirements
Function: Engineering
Experience Level: Mid-Senior Level