AI Backend Engineer - Digital Banking

Senior backend engineering role supporting Digital Banking scale, resilience, delivery acceleration, and platform modernization Role summary: This role strengthens the Digital Banking engineering bench with senior hands-on backend expertise across secure microservices, APIs, distributed systems, Kafka, reliability, and production readiness. The position supports faster delivery of banking capabilities while reducing operational risk through stronger engineering quality, observability, scalability, and technical leadership. GenAI/RAG/LLM exposure is positioned as a primary differentiator, not a core hiring requirement., Joining the Digital Banking technology team means shaping secure, scalable, and resilient banking capabilities that support customer-facing financial experiences. In this role, you will apply deep backend engineering expertise across the software development lifecycle while partnering with product, architecture, operations, and business stakeholders to deliver high-quality platform services. The Digital Banking platform focuses on accelerating financial innovation and enabling new banking products while maintaining high availability, resilience, observability, and engineering quality. The team builds and modernizes backend services, APIs, event-driven workflows, and integration patterns that support reliable delivery at scale. As part of the team As part of the team, you will work in a culture focused on engineering excellence, shared ownership, and continuous improvement. You will stay hands-on while influencing architecture, mentoring engineers, and partnering across product and business teams to deliver secure, customer-facing financial capabilities. Responsibilities Design, develop, and maintain backend services for Digital Banking platforms that support high transaction volume, security, scalability, and reliability. Lead distributed systems design across service decomposition, asynchronous communication, fault tolerance, idempotency, backpressure, consistency of trade-offs, and graceful degradation. Build Java microservices, REST APIs, batch jobs, and event-driven workflows using modern engineering patterns. Contribute to workflow implementations and champion workflow orchestration best practices across services. Engage in hands-on design and development as part of a nimble agile team, contributing to architecture, code quality, delivery execution, and operational readiness. Ensure platforms are safely extensible, scalable, observable, reliable, and aligned to SLAs for internal and external users. Design solutions that are testable, intuitive, maintainable, and easy for engineering teams to operate over time. Actively participate in design reviews, code reviews, and engineering discussions for key components and cross-enterprise initiatives. Partner with stakeholders to translate business capabilities into secure, performant, and maintainable technical solutions. Provide technical mentorship to engineers, help teams overcome complex problems, and raise engineering standards across the team.

8+ years of software development experience; bachelor''s or master''s degree in computer science, computer engineering, or related technical discipline preferred. Strong hands-on backend engineering experience with Java and its frameworks. Extensive hands-on experience building distributed applications and operating scalable, low-latency services across complex enterprise environments. Strong understanding of REST APIs, JSON, XML, service contracts, integration patterns, and API lifecycle practices. Hands-on experience with Spring, Spring Boot, Spring Batch, JUnit, JDBC, Gradle/Maven, Jenkins, and modern CI/CD practices. Experience with Kafka or similar streaming/event-driven technologies; Kafka Streams experience is highly desirable. Practical knowledge of distributed systems, caching, high availability techniques, multi-threading, and performance analysis. Experience with relational and NoSQL databases such as PostgreSQL, MongoDB, and similar data platforms. Commitment to continuous integration, automated/repeatable testing, secure coding practices, and collaborative engineering environments. Ability to think abstractly, work through ambiguous problems, and enable business capabilities through pragmatic technical decisions. Excellent written and verbal communication skills with the ability to partner across engineering, product, architecture, and operations. Experience mentoring, coaching, and influencing engineers while remaining hands-on with design and development. You have strong expertise with the following: Docker, Github capabilities, and deployment automation in modern platform environments. Payment systems, real-time transaction platforms, customer account management, data/reporting, or fintech APIs. Full-stack development exposure and/or Data side experience with Python, Hadoop, or Spark. Experience with in-memory computing solutions and advanced performance optimization techniques. Leadership experience in a fast-paced development environment, including technical ownership, design facilitation, and delivery of accountability. Big Plus if you have: The primary focus of this role is core backend engineering. GenAI experience is a preferred differentiator for candidates who can apply AI responsibly in regulated enterprise environments. Exposure to LLM-powered applications, prompt engineering, structured outputs, or tool/function calling. Familiarity with Retrieval-Augmented Generation patterns such as ingestion, chunking, embeddings, vector search, reranking, and relevance tuning. Awareness of GenAI guardrails, evaluation approaches, hallucination mitigation, PII handling, prompt injection risks, and data leakage controls. Experience with AWS services such as EC2, RDS, S3, and SQS, along with cloud-native architecture and DevOps practices. Experience working with governance practices such as data governance, secure data access, shared schemas, service contracts, auditability, compliance controls, and risk-aware engineering in regulated environments. Experience contributing to platform architecture across shared services, APIs, identity, payments, partner ecosystems, data governance, and modernization efforts. Core Technology Stack Area Technologies / Capabilities Backend Java (JDK 17-25), Spring frameworks, Spring Boot, REST / RPC APIs, Reactive frameworks Build & Test JUnit, Gradle, Maven, Jenkins, GitLab, CI/CD, automated testing Data PostgreSQL, MongoDB, Redis, Cassandra Streaming Kafka, Kafka Streams, event-driven architecture, workflow orchestration Platform Docker, high availability, distributed systems design, fault tolerance, resiliency patterns, observability, performance analysis Good-to-have GenAI LLM apps, RAG, embeddings, vector search, tool/function calling, MCP concepts, AI guardrails Good-to-have Cloud / DevOps AWS EC2, RDS, S3, SQS, cloud-native architecture, DevOps practices Good-to-have Governance Data governance, secure data access, shared schemas, service contracts, auditability, compliance controls, risk-aware engineering Good-to-have Platform Architecture Shared services, APIs, identity, payments, partner ecosystems, data governance, modernization At the core of Software Engineering, you should demonstrate: Reliable backend delivery that improves speed-to-market for Digital Banking products. Architecture quality, code quality, testing discipline, and operational readiness across the software development lifecycle. Demonstrates strong judgment in distributed systems of trade-offs, including latency, throughput, consistency, scalability, and failure of recovery. Balances hands-on delivery with technical leadership, mentorship, and cross-team collaboration. Designs pragmatic, scalable solutions that support business growth while meeting security, compliance, and reliability expectations. A passion for documenting how systems work and making complex services easier for teams to operate and evolve.