Backend Self Service Software Engineer

JD:
The Digital Banking and Payments team is responsible for our Card Payments Processing and Digital Bank products. We are currently building platforms responsible for ACH, Wire, Bill Pay, Zelle, Debit, Checking, and Savings applications that allows teams to create products at scale and allow digital channels to deliver compelling experiences in a dramatically faster fashion
We're building a next-generation orchestration and automation platform to support thousands of business processes across the enterprise. This isn't about coding one-off automations - it's about creating the platform, APIs, and orchestration primitives that other developer teams will use to define, run, and scale their business processes.
As the Lead Backend Engineer , you'll be hands-on in Kotlin every day, designing platform services, integrating workflow orchestration frameworks, and enabling GenAI-powered intent parsing and decision nodes. You need to understand complexity, trade offs and scaling.





Responsibilities:

• Design and build backend platform services in Kotlin for ingestion, orchestration, RBAC, monitoring, and developer tooling.
• Implement and optimize workflow orchestration frameworks (e.g., Temporal, Cadence, Camunda, Argo).
• Provide scalable APIs and abstractions that empower other teams to build workflows on the platform.
• Integrate GenAI/NLP pipelines for intent parsing, process matching, and intelligent decisioning.
• Champion developer experience (DX) through tooling, CI/CD improvements, and observability.
• Mentor backend engineers, lead design reviews, and guide technical decisions.
• Collaborate closely with frontend, product, and process analysts to ensure platform adoption and impact.

Qualifications:

• Bachelor's degree in computer science, Engineering, Data Science, or related field (or equivalent experience).
• 10+ years of backend engineering experience, with strong Kotlin/JVM expertise.
• Proven track record building platforms, frameworks, or orchestration services (not just applications).
• Hands-on experience with workflow orchestration systems (Temporal, Cadence, Camunda, Argo, or similar).
• Deep knowledge of distributed systems, API design, and event-driven architectures.
• Practical experience integrating GenAI/NLP into backend systems.
• Experience with RBAC/security models in multi-tenant or enterprise environments.