Senior Platform Engineer (m/f/d) at Allianz Insurance

Barcelona, Catalonia, Spain -

Full Time

Start Date

Immediate

Expiry Date

14 Aug, 26

Salary

0.0

Posted On

16 May, 26

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Python, Kubernetes, RESTful APIs, Azure, AWS, Databricks, Terraform, OAuth 2.0, JWT, RBAC, Kafka, MLflow, Delta Lake, GenAI, Distributed Systems, Backend Engineering

Industry

Financial Services

Description

Allianz Services is proud to serve and be part of Allianz Group, one of the world's leading insurers and asset managers. Our global footprint, with more than 8800 employees located across ten countries and four continents, enables us to unlock value for our partners across the insurance value chain and deliver superior client experience within Allianz Group. At Allianz Services, we have a strong specialization in core insurance operations, shared services, business analytics, engineering, and management consulting. Our people and our trusted relationships with partners are what matter most. These are rooted in our values of compassion, integrity, and expertise and we strive to continuously evolve, improve, and deliver excellence while contributing successfully to the transformation of Allianz. Caring actively for the environment, for people, and for our customers is what makes us a great place to work and together we are shaping a better and more caring tomorrow. Allianz Services is a company which belongs to the legal entity, Allianz Technology SE. Role overview We are looking for a Senior Platform Engineer to join the Data and AI Transformation Engineering team, responsible for designing and building scalable backend platforms that expose AI and automation capabilities as reliable, production grade services. The role focuses on developing API driven systems deployed on Kubernetes, combining AI driven components with deterministic logic to support complex transformation and automation use cases across multiple business units. Operating in a regulated financial services environment, the role requires a strong engineering mindset with compliance, governance, and responsible use of AI treated as core design principles. What you do: Design and maintain RESTful APIs with robust versioning strategies, ensuring stability as model behaviour evolves across releases Define structured, validated response schemas that deliver deterministic, auditable outputs suitable for enterprise consumption Implement streaming response patterns (SSE / chunked HTTP) to enable real-time model output delivery to frontends and downstream systems Implement authentication and authorisation frameworks (OAuth 2.0, JWT, RBAC, scopes) including service principal patterns for cloud-to-cloud integration across Azure, AWS, and Databricks Enforce data controls at the API layer — including input sanitisation, output filtering, and guardrails — ensuring responses meet compliance standards before leaving the system Build audit logging into the API contract so that every request and response is fully traceable for regulatory purposes Design background job patterns that return immediately to callers while model inference executes asynchronously Integrate with message queues and event-driven architectures (Azure Service Bus, SQS, Kafka) for pipeline orchestration Implement polling and webhook callback mechanisms to deliver results without blocking consumers Establish structured logging on every API call — capturing inputs, outputs, latency, and model version metadata Integrate with enterprise monitoring platforms (Datadog, Azure Monitor, CloudWatch) to ensure full-stack visibility Implement drift detection hooks that flag when model outputs deviate from expected patterns Manage versioned model endpoints, enabling seamless deployment of new model versions without breaking existing API consumers Develop automated testing strategies for non-deterministic outputs, including contract tests, output validation, and regression benchmarks Deploy containerised APIs on Kubernetes (AKS/EKS) with health checks, autoscaling, and production-grade reliability Wrap managed AI services (Databricks Model Serving, Azure OpenAI, AWS Bedrock) behind clean, internal API contracts Abstract cloud-specific SDKs to provide business units with a unified interface, regardless of the underlying model provider What you bring: University degree in Data Science, Data Engineering, Computer Science, Mathematics, Statistics, or a related field (or equivalent experience). 7+ years of experience in backend engineering with Python, with a proven track record of delivering AI/ML, GenAI, and agentic systems into enterprise production environments (beyond prototypes or proofs of concept). Hands on experience with cloud based AI services across Azure and AWS, including strong expertise in Databricks (MLflow, Delta Lake, Model Serving). Strong background in designing clean, versioned APIs and building distributed systems, including asynchronous patterns, background processing, and message based architectures. Proven experience deploying and operating services on Kubernetes, managing infrastructure using Terraform, and treating observability, structured logging, and monitoring as standard engineering practices. Experience working in regulated environments, where auditability, data controls, security, and compliance are core engineering requirements. Demonstrated ownership mindset: able to take systems from design through production and incident resolution, collaborate across business units, and create reusable platform patterns that enable other teams. Good level of English (required). Other languages (e.g. Spanish or additional European languages) are nice to have. We highly welcome candidates with a genuine interest and affinity for Information Technology (IT) and (Generative) Artificial Intelligence (Gen)AI, as these attributes are considered valuable assets to our team. What we offer: We offer a hybrid work model which recognizes the value of striking a balance between in-person collaboration and remote working incl. up to 25 days per year working from abroad We believe in rewarding performance and our compensation and benefits package includes a company bonus scheme, pension, employee shares program and multiple employee discounts (details vary by location) From career development and digital learning programs to international career mobility, we offer lifelong learning for our employees worldwide and an environment where innovation, delivery and empowerment are fostered Flexible working, health and wellbeing offers (including healthcare and parental leave benefits) support to balance family and career and help our people return from career breaks with experience that nothing else can teach. Allianz Group is one of the most trusted insurance and asset management companies in the world. Caring for our employees, their ambitions, dreams and challenges is what makes us a unique employer. We are united by a shared commitment: to put our customers first and at the center of everything we do. Their needs inspire our thinking and guide our actions. Together, we can build an environment where everyone feels empowered and confident to explore, grow and shape a better future – for our customers and for the world around us. At Allianz, we stand for unity: we believe that a united world is a more prosperous world, and we are dedicated to consistently advocating for equal opportunities for all. The foundation for this is our inclusive workplace, where people and performance both matter, and where integrity, fairness, inclusion and trust are at the heart of our culture. We therefore welcome applications regardless of ethnicity or cultural Internal background, age, gender, nationality, religion, social class, disability or sexual orientation, or any other characteristics protected under applicable local laws and regulations. Join us. Let’s care for tomorrow.

Responsibilities

Design and build scalable backend platforms and RESTful APIs to expose AI and automation capabilities as production-grade services. Implement secure, compliant, and observable systems using Kubernetes and cloud-native AI services across Azure and AWS.