About this role:(Principal Engineer - Java with Gen AI)
We are hiring a Principal Engineer with deep Java ecosystem expertise to architect and scale enterprise-grade AI systems operating at global banking scale.
This role requires a hands-on technologist who can combine strong Java-based distributed systems engineering with modern GenAI architecture patterns in a regulated financial environment.
You will own foundational platform components that integrate LLM-driven capabilities into high-throughput, mission-critical banking systems.
In this role, you will:
- Act as an advisor to leadership to develop or influence applications, network, information security, database, operating systems, or web technologies for highly complex business and technical needs across multiple groups
- Lead the strategy and resolution of highly complex and unique challenges requiring in-depth evaluation across multiple areas or the enterprise, delivering solutions that are long-term, large-scale and require vision, creativity, innovation, advanced analytical and inductive thinking
- Translate advanced technology experience, an in-depth knowledge of the organizations tactical and strategic business objectives, the enterprise technological environment, the organization structure, and strategic technological opportunities and requirements into technical engineering solutions
- Provide vision, direction and expertise to leadership on implementing innovative and significant business solutions
- Maintain knowledge of industry best practices and new technologies and recommends innovations that enhance operations or provide a competitive advantage to the organization
- Strategically engage with all levels of professionals and managers across the enterprise and serve as an expert advisor to leadership
Required Qualifications:
- 15+ years of Engineering experience, or equivalent demonstrated through one or a combination of the following: work experience, training, military experience, education
Desired Qualifications:
- Strong hands-on expertise in Java ecosystem (Spring Boot, REST APIs, microservices, concurrency, performance tuning) and Python
- Proven experience designing large-scale distributed systems in production
- 1- 2 years of experience delivering GenAI systems, including hands-on work with:
- Applications powered by LLMs
- RAG architectures
- Embeddings and vector databases
- Agent frameworks and orchestration
- Experience integrating AI services into enterprise backend platforms
- Strong cloud-native experience (GCP, Azure)
- Ability to influence architectural decisions across complex systems
- Experience in Banking/Financial services domains (e.g. commercial or corporate, Payments, Treasury, lending, FX)
- Experience implementing AI governance, risk, and model validation frameworks
- Familiarity with event-driven architectures (Kafka or similar)
- Experience modernizing legacy Java systems with AI augmentation
- Excellent communication skills with experience engaging senior stakeholders
Job Expectations:
- Deployment of GenAI services embedded into core Java-based banking platforms
- Strong alignment between AI capabilities and commercial banking product strategy
- Production-grade GenAI applications integrated into Java-based enterprise platforms
- RAG pipelines, agent orchestration layers, and AI service abstractions callable from core Java systems
- Secure, compliant Open Banking APIs powering high-volume enterprise clients
- Observability, resilience, and governance frameworks for AI-enabled services
- Design and implement high-performance distributed systems primarily in Java (Spring Boot, microservices architecture), ReactJS and MicroFrontends
- Integrate LLMs, RAG pipelines, and AI orchestration frameworks into enterprise Java systems
- Lead deep technical design reviews across backend, API, and AI integration layers
- Partner with Product and Business leaders to shape AI-enabled banking capabilities
- Mentor senior engineers and elevate engineering rigor across the organization
- You will solve hard engineering problems inside regulated, mission-critical environments
- You will influence AI platform direction at scale and build durable systems — not prototypes
