Principal Engineer

• 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
• Translate advanced technology experience 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
• Strategically engage with all levels of professionals and managers across the enterprise
• Own overall architecture and design of Product's application footprint, complex capabilities, governance and risk controls, and resiliency improvements
• Lead and drive bank's digital transformational journey leveraging newer technologies like AI and ML
• Act as a technical bridge between engineering, product, research, and compliance teams
• Mentor senior engineers and data scientists
• Remove key architectural bottlenecks of global teams and federated customers
• Design scalable, reusable solution architectures and pipelines
• Continuously evaluate and integrate new tools, frameworks, and models

• 7+ years of Engineering experience, or equivalent demonstrated through work experience, training, military experience, education
• Bachelor's or master's degree in computer science engineering, or a related technical field
• Experience in provisioning, operating, and maintaining systems running in the cloud environments (GCP, Azure)
• Deep understanding of microservice architecture, cloud-native platforms, and infrastructure-as-code
• Expertise in Ansible, CI/CD pipelines, observability tools (e.g., Prometheus, Grafana, ELK, Datadog), and incident management frameworks
• Familiarity with Enterprise level AI and automation tooling
• Strong understanding of governance, compliance, and operational risk management in engineering environments
• Experience in Generative AI tech like Retrieval-Augmented Generation (RAG) – design end-to-end pipelines (Vector DBs, chunking, embedding, retrieval, context injection) to ground LLM responses on enterprise knowledge
• Ability to spot emerging tech trends and drive Proof of Concepts or pilot solutions
• Must be able to work on multiple projects and consistently meet project deadlines
• Interpersonal and communication skills, able to build rapport and communicate effectively at all levels and across disciplines
• Ability to own the end-to-end Ai/ML lifecycle—design, build, deploy, and maintain scalable agent solutions
• Strong software development skills, particularly in Python, with experience working with AI frameworks (like: LangChain, LangGraph)
• Knowledge of ML, NLP, Information Retrieval, Recommender Systems and LLMs
• Prior knowledge of working with enterprise platforms and building solutions, in consideration to enterprise-wide guidelines & standards

Embed Generative Ai and Agentic Ai into day-to-day business processes to lift efficiency and employee productivity

• Equal opportunity employment
• Accommodation for applicants with disabilities available upon request
• Drug free workplace