Software Engineer

Job details

Job ID

69429

Collaborate with Product Managers and stakeholders to translate business requirements into technical solutions.
Design and develop cloud-native applications, APIs, and microservices using Java and Spring Boot.
Apply modern architecture patterns including Domain-Driven Design (DDD), Event-Driven Architecture, CQRS, and Hexagonal Architecture.
Produce technical designs, API specifications, and architecture documentation.

Leverage AI development tools such as GitHub Copilot, Claude Code, Cursor, or similar platforms to improve engineering productivity.
Practice specification-driven development using API contracts, acceptance criteria, and automated testing.
Review, validate, and maintain accountability for all AI-generated code and design recommendations.
Contribute to reusable engineering standards, templates, and automation that enhance software delivery quality.

Design and develop AI-enabled capabilities using Vertex AI, Azure OpenAI, or similar platforms.
Implement retrieval-augmented generation (RAG), intelligent search, document understanding, and agent-assisted workflows.
Build model evaluation, monitoring, and testing frameworks to ensure reliable AI outcomes.
Implement responsible AI controls, including privacy, security, and human oversight mechanisms.

Build and deploy applications on Google Cloud Platform (GCP).
Develop and maintain CI/CD pipelines using GitHub Actions, Cloud Build, or equivalent tools.
Utilize Infrastructure as Code (Terraform) and container orchestration platforms such as Kubernetes.
Apply security best practices throughout the software development lifecycle.

Monitor and support production systems using tools such as Dynatrace, Splunk, Prometheus, and Grafana.
Troubleshoot application, platform, and infrastructure issues.
Continuously improve performance, reliability, scalability, and operational efficiency.
Support high availability, disaster recovery, and resilience requirements.

Bachelor's degree in Engineering, Computer Science, Information Technology, or related field.
8+ years of software engineering experience.
Strong expertise in Java and Spring Boot microservices.
Experience designing and developing RESTful APIs.
Hands-on experience with containerization and Kubernetes.
Experience with public cloud platforms, preferably Google Cloud Platform (GCP).
Experience with SQL and NoSQL databases.
Strong understanding of CI/CD pipelines and automated testing.
Knowledge of Domain-Driven Design (DDD), Event-Driven Architecture, and modern application architecture patterns.
Experience using AI-assisted software development tools such as GitHub Copilot, Cursor, Claude Code, or similar solutions.

Experience with Vertex AI, Azure OpenAI, or other LLM-based platforms.
Knowledge of CQRS and Hexagonal Architecture.
Experience with Terraform and Infrastructure as Code.
Familiarity with DevSecOps tools including SonarQube, FOSSA, Cycode, and 42Crunch.
Knowledge of AI governance, model evaluation, and responsible AI practices.
Experience in financial services or other regulated industries.

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