Staff Software Engineer (API Integrations/AI Integration)

We are seeking a Staff Software Engineer – Integration & Platform (Java/Spring) to serve as a technical anchor for our Integration & Platform team. This individual will lead the architecture and evolution of critical backend services, define and uphold engineering standards, and drive the modernization of our Java/Spring Boot ecosystem toward cloud-native and AI-enabled workflows.

The ideal candidate brings deep expertise in distributed systems, cloud infrastructure, and API/integration design, along with strong leadership capabilities. They will possess exceptional communication and problem-solving skills and thrive in a fast-paced, highly collaborative environment while influencing technical direction without direct authority.

• Own, design, and evolve distributed backend services using Java and Spring Boot
• Architect systems for scalability, reliability, performance, and observability
• Drive and document architectural decisions through ADRs, RFCs, and other technical artifacts
• Establish and enforce engineering standards, design patterns, and best practices

• Define and implement cloud-native architecture patterns across environments
• Lead adoption and optimization of:
• Infrastructure as Code (Terraform, CDK)
• Containerization and orchestration (Kubernetes)
• Service mesh technologies (Istio, Linkerd)
• Optimize systems for resilience, cost efficiency, and operational excellence

• Design, build, and scale multi-tenant RESTful APIs and integration services
• Lead modernization initiatives, including legacy SOAP to REST migrations
• Define, standardize, and enforce API governance and best practices
• Architect and implement integration patterns including:
• Webhooks
• Event-driven systems (Kafka, Kinesis)
• External system connectivity frameworks

• Design and implement Model Context Protocol (MCP) server/client patterns
• Enable secure interactions between LLM agents and internal systems, databases, and tools
• Ensure AI integrations are safe, observable, governed, and scalable
• Contribute to evolving AI-driven platform capabilities

• Elevate standards for code quality, peer reviews, and maintainability
• Define and promote robust testing strategies (unit, integration, performance)
• Improve observability, monitoring, and on-call practices
• Mentor senior engineers and provide technical leadership across teams

• Partner closely with Product, Infrastructure, and Integration teams
• Translate ambiguous business requirements into clear technical solutions and roadmaps
• Communicate technical trade-offs effectively to both technical and non-technical stakeholders
• Actively participate in Agile/Scrum ceremonies and planning processes

• Experience leading large-scale platform modernization initiatives
• Strong documentation practices and technical writing skills
• Passion for emerging technologies, particularly AI-driven development patterns
• Excellent collaboration and stakeholder management abilities
• Continuous learner with a growth mindset and a bias toward innovation

• 8+ years of hands-on Java development in production environments
• Deep expertise with Spring Boot and Spring Cloud ecosystems
• Strong understanding of JVM internals, performance tuning, concurrency, and multithreading

• Hands-on experience with AWS, GCP, or Azure
• Strong experience with Kubernetes and containerized deployments
• Proficiency in Infrastructure as Code (Terraform or CDK)
• Experience building and maintaining CI/CD pipelines at scale
• Familiarity with service mesh architectures

• Proven experience designing and scaling distributed systems
• Strong understanding of event-driven architectures (Kafka, Kinesis)
• Expertise in API design (REST, GraphQL, and legacy SOAP systems)
• Solid data modeling experience (SQL and NoSQL databases)
• Strong foundation in security principles (authentication, authorization, secrets management)

• Experience with distributed tracing (OpenTelemetry)
• Familiarity with logging and monitoring tools (Prometheus, Grafana)
• Experience defining and managing SLOs/SLAs
• Participation in incident response and postmortem processes

• Experience or exposure to Model Context Protocol (MCP)
• Familiarity with LLM integrations, agent workflows, and AI-enabled systems
• Understanding of secure design principles for AI interactions

• Demonstrated ability to influence technical direction without direct authority
• Strong mentorship, coaching, and team development skills
• Ability to operate effectively in ambiguous and fast-paced environments