The AI Gateway Engineer role requires development, maintaining, updating, and supporting Global AI Platform Services, Tools, and AI Gateways Management Globally. With focus on Microsoft Azure Cloud Platform, API development using .NET C#, Python, Node JS, Primarily and good to have would be Angular Programming Stacks, and mobile application architecture design and implementation.

Additionally, this role involves implementing and automating DevOps practices, working with Agile Teams in fast-paced projects, and demonstrating quick learning abilities. Responsible to produce and maintain System Requirements and Specifications, leading development efforts with the product owner and scrum master to achieve application capability goals. Ensure proper backlog user stories creation and work is distributed with clear milestones and deadlines. Support Onboarding and Production Support Teams on bug fixes and user feedback. Provide architectural reviews, recommendations, best practices, and standards to Teams Developing AI Solutions. Follow AI Platform Onboarding Process to ensure adherence to Chubb's LLM, MCP, Agent, Knowledge Sources, API, Security, Identity, Architecture, Infrastructure, and DevOps standards and best practices. This role requires hands-on ability to create, maintain, and support AI Platform Services, Components, Tools, and Portals, as well as collaborating and coordinating project efforts with other Global Engineering Teams at Chubb.

Responsibilities

• Create, maintain, and support AI Platform Services, Components, Tools, and Portals, as well as collaborating and coordinating project efforts with other Global Engineering Teams at Chubb.
• Develop web applications using Python and .NET core with the latest frameworks.
• Ability to debug and resolve application challenges.
• Ability to write Database queries, stored procedures, and functions.
• Involvement in the full development life cycle, including design, coding, testing, building, QA, deployment, and maintenance.

Qualifications

• Strong Knowledge of Azure API Management
• Working Knowledge of AI Gateway Patterns, RAG Patterns, MCP Patterns, Agent Patterns, LLM Patterns
• A2A and MCP Protocols
• Strong knowledge of SOA and Micro Services with a focus on Kubernetes and VMware Tanzu Container Orchestrators
• Strong knowledge and understanding of Web API hosting architecture and troubleshooting connectivity and errors.
• Strong Knowledge of Cloud Computing with hands-on experience with Microsoft Azure Services, Azure Security, and Cloud-to-On Premise Integration
• Strong knowledge of setting up the Azure environment including App Services, API management, Batch, Storage, Service Bus, Relays, Security, Queue, Redis Cache, etc.
• Strong knowledge of Azure file storage, security, scanning, and transferring files across environments
• Strong working knowledge of App Insights, Log Analytics, Open Search
• Strong working knowledge of distributed event streaming platforms like Kafka, Event Hub, and Service Bus
• Strong hands-on experience with NOSQL Databases like Cosmos DB, Mongo DB
• Strong hands-on experience with SQL Server and T-SQL
• Strong hands-on experience developing Web Services REST API, XML, and JSON
• Knowledge of Azure Service Architecture development, deployment, and monitoring
• Hands-on experience in developing Azure PowerShell scripts for deployments, Insights, and Diagnostics
• Strong knowledge of Azure security, performance tuning, and optimization
• Experience with web API best practices (caching, headers, versioning, etc.)
• Experience with web operations best practices (monitoring, logging, etc.)
• Experience working on data providers and APIs for mobile and web clients.
• Strong understanding of security, performance tuning, and optimization
• Experience working with agile methodologies and rapid iteration.
• Familiarity with agile methodologies Git-flow processes and source control
• Experience with DevOps practices/methodologies

Required Skillset

Candidate must have worked, at least in last two projects, demonstrating proficiency with the below

• Ability to clearly communicate and lead to successful outcomes.
• Ability to work collaboratively in a team-oriented environment.
• Ability to convey Critical Thinking
• Excellent grasp of SOLID Principle
• Familiarity with Object-Oriented Design (OOD) principles
• Excellent knowledge of OOPS concepts
• Excellent understanding of HTTP Status Codes best practices
• Knowledge of building RESTful APIs
• Knowledge of cloud technologies, preferably Azure
• Programming/coding, developing application design, APIs for middleware Framework modules for mobile platforms.
• Knowledge of Design Patterns (Adapter, Singleton, Prototype, Decorator, Composite, Abstract Factory)
• Familiarity with frameworks, design guidelines, and cross-platform tools
• Familiarity with .NET core, MVC, and Entity frameworks
• Experience building applications using JAVA EE and Spring MVC
• Experience with OpenSearch for large dataset analytics, search applications, and log monitoring
• Experience with Apache Camel and Apache Kafka
• Working knowledge of mobile application development, including User-friendly design, performance improvement, documenting code, refactoring, continuous integration and deployment, and unit testing
• Experience with JAVA, C#, .Net Core, MVC, jQuery, JavaScript, TSQL, Angular, HTML, and LINQ
• Excellent working knowledge of Visual Studio 2021, Eclipse, VS Code, and SQL Server
• Hands-on experience writing SQL queries, stored procedures, and functions.
• I have knowledge of version control using GitHub and TFS, VSTS, Jenkins.

Desired AI Skillset

• Machine Learning Fundamentals Understanding supervised, unsupervised, and reinforcement learning algorithms forms the foundation of AI development. This includes knowledge of regression, classification, clustering, and neural networks. Engineers must grasp model training, validation, testing procedures, overfitting prevention, and hyperparameter tuning. Proficiency in evaluating model performance using appropriate metrics is essential for building effective AI solutions.
• Deep Learning Frameworks Mastery of TensorFlow, PyTorch, or Keras enables engineers to build sophisticated neural networks efficiently. These frameworks provide pre-built layers, optimization algorithms, and tools for model deployment. Understanding computational graphs, automatic differentiation, GPU acceleration, and transfer learning techniques allows developers to create scalable deep learning applications for computer vision, NLP, and other domains.
• Natural Language Processing (NLP) Expertise in text processing, tokenization, word embeddings, and transformer architectures like BERT and GPT is crucial. Engineers should understand sentiment analysis, named entity recognition, machine translation, and text generation. Familiarity with libraries like spaCy, NLTK, and Hugging Face Transformers enables building chatbots, content analyzers, and language understanding systems for modern applications.
• Computer Vision Knowledge of image processing, object detection, segmentation, and facial recognition techniques is vital. Engineers should understand convolutional neural networks (CNNs), image augmentation, and architectures like ResNet, YOLO, and U-Net. Experience with OpenCV and modern frameworks allows development of applications in autonomous vehicles, medical imaging, surveillance, and augmented reality systems.
• Data Engineering & Preprocessing Ability to collect, clean, transform, and prepare large datasets for AI model training is fundamental. This includes handling missing values, feature engineering, normalization, and data augmentation. Engineers must work with SQL, NoSQL databases, data pipelines, and tools like Pandas, NumPy, and Apache Spark to ensure high-quality data feeds AI systems effectively.
• MLOps & Model Deployment Skills in containerization using Docker, orchestration with Kubernetes, and CI/CD pipelines for machine learning models are essential. Engineers should understand model versioning, monitoring, A/B testing, and automated retraining workflows. Familiarity with cloud platforms (AWS, Azure, GCP), MLflow, and serving frameworks ensures reliable, scalable deployment of AI models in production environments.
• AI Ethics & Responsible AI Understanding bias detection, fairness metrics, privacy preservation, and ethical implications of AI systems is increasingly critical. Engineers must implement explainable AI techniques, ensure GDPR compliance, and consider societal impacts. Knowledge of differential privacy, federated learning, and fairness-aware algorithms helps build trustworthy, transparent AI solutions that respect user rights and dignity.
• Programming & Software Architecture Strong proficiency in Python, with knowledge of Python, C#, or C++ for performance-critical applications, is fundamental. LangChain, LangFuse. understanding object-oriented design, design patterns, microservices architecture, and API development ensures scalable AI systems. Engineers should write clean, maintainable code, implement unit tests, and follow best practices for version control, documentation, and collaborative development.

This job posting is for an existing vacancy: the approximate salary for this role is positioned within the range of $130,000 to $160,000. The specific offer will depend on an applicant’s skills and other factors, including prior experience, qualifications, anticipated contribution to the role, location, and internal equity. The Company reserves the right to fill this position at a level above or below the level indicated.

Chubb Canada does not use artificial intelligence (AI) tools to assess, screen, or select applicants.

At Chubb we are committed to providing equal employment opportunities to all employees and applicants. It is our policy to provide equal employment opportunities to employees and applicants based on job-related qualifications and ability to perform a job. If you require an accommodation during the hiring process or upon hire, please inform Human Resources. If a selected applicant requests accommodation during the recruitment process, Chubb will consult with the applicant in order to provide suitable accommodation that takes into account the applicant’s accessibility needs.