Software Engineer

Product Development & Architecture

• 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.

AI-Augmented Software Engineering

• 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.

AI-Powered Product Features

• 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.

Cloud Engineering & DevSecOps

• 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.

Reliability, Operations & Observability

• 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.

Required

• 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.

Preferred

• 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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