Accountabilities

• Design, develop, and maintain software solutions: Build robust, maintainable, and scalable applications using object-oriented programming principles, applying sound engineering judgment and established software development best practices.
• Drive architectural improvements: Contribute to technical strategy, facilitate architecture discussions, design scalable systems, and modernize legacy applications through thoughtful abstractions and maintainable design patterns.
• Leverage AI-assisted engineering: Integrate AI coding and review assistants into daily workflows, critically evaluating generated output and identifying responsible opportunities to automate code reviews, documentation, issue triage, and other repetitive engineering tasks.
• Own messaging and event infrastructure: Design, maintain, and evolve reliable messaging systems using Apache Kafka and other message-bus technologies to support downstream services and event-driven architectures.
• Build and manage cloud infrastructure: Develop and support cloud-based solutions using AWS services, including Fargate, Bedrock, EC2, ECS, SNS/SQS, RDS, and Elasticsearch.
• Strengthen DevOps and deployment practices: Work with Docker, Kubernetes, Terraform, and deployment automation tools to improve infrastructure reliability, scalability, and operational efficiency.
• Manage data systems: Apply SQL and NoSQL expertise to build and maintain efficient data solutions that support application performance, scalability, and reliability.
• Ensure production reliability: Participate in and lead rotational on-call responsibilities, implement proactive monitoring, investigate incidents, and continuously improve system resilience and operational practices.
• Collaborate across teams: Partner with engineering, internal tooling, and cross-functional teams to shape technical roadmaps, improve developer experience, share practical feedback, and influence the evolution of AI-driven engineering tools.
• Promote documentation and knowledge sharing: Maintain clear technical documentation and architectural decision records, contribute to code reviews, and encourage consistent engineering standards across teams.
• Mentor and develop engineers: Coach teammates, share technical expertise, and foster a collaborative culture focused on continuous improvement, curiosity, and high-quality delivery.
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Requirements

• Extensive software engineering experience: At least 9 years of professional software development experience, with strong commercial expertise in object-oriented programming.
• Strong programming skills: Advanced proficiency in Java and experience with at least one additional programming language, preferably C#.
• Distributed systems expertise: Hands-on experience with Apache Kafka or comparable messaging systems, microservices architectures, and event-driven application design.
• System design and architecture: A strong understanding of scalable system design, architectural patterns, software maintainability, and modern engineering principles.
• Cloud technology experience: Practical experience with AWS services and cloud-native application development. Familiarity with services such as Fargate, Bedrock, EC2, ECS, SNS/SQS, RDS, and Elasticsearch is advantageous.
• DevOps and infrastructure skills: Experience with containerization, particularly Docker and Kubernetes, infrastructure as code using Terraform, and automated deployment processes.
• Database expertise: Confidence working with both relational SQL databases and NoSQL technologies, including the ability to design efficient and scalable data solutions.
• AI-augmented development experience: Regular, hands-on use of AI-powered coding or code-review assistants, with the ability to assess their output critically, validate results, and make informed decisions about when to adopt or reject suggestions.