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The position leads architecture and technology strategy for AI initiatives, establishing frameworks and platforms for data engineering, regulatory compliance, and fostering innovation in modern engineering practices. It collaborates across teams, drives process optimization, and builds scalable GenAI applications.
Job Responsibility:
Establish and lead an elite engineering culture focused on building core Platform components across Application and Service Frameworks, UI, and Data Engineering for use across the organization
Create technology solutions and work in partnership with multiple IT teams and with Cloud providers to accelerate public cloud Adoption and harness associated emerging technologies
Drive data standardization efforts in alignment with regulatory requirements, consent orders, and enterprise data policies
Ensure data lineage, quality, and governance compliance across all critical data elements (CDEs)
Collaborate with Risk, Compliance, and Regulatory teams to address consent order requirements related to data controls, reconciliation, and validation
Implement data quality frameworks, metadata management, and lineage tracking for improved data transparency and regulatory reporting
Optimize data ingestion, transformation, and processing pipelines using streaming and batch processing methodologies
Develop and enforce data security and privacy controls to meet internal and external regulatory expectations
Work closely with cross-functional teams to automate data reconciliation and anomaly detection
Architect and oversee the development of agentic GenAI applications, ensuring high-quality, scalable, and secure solutions Design and manage data pipelines and model integration, ensuring optimal performance and data quality Drive rapid prototyping, experimentation, and iteration of GenAI features and capabilities
Ensure compliance with security and regulatory standards relevant to AI in financial services Actively contribute to coding, code reviews, and technical problem-solving alongside your team
Guide and mentor developers, fostering skill growth and best practices in AI/ML and software engineering Report on project progress, technical challenges, and team needs to senior leadership
Work across the Trade Working Capital Solutions businesses to forge deep technical partnerships with senior technical leaders and practitioners
Partner with Engineering teams across Citi to create an environment that provides an optimal Developer Experience for, from IDE and CI/CD through to IaaS provisioning and Cloud Native Service onboarding frameworks
Foster a culture of innovation and engineering excellence across the Enterprise: modern engineering practices, adoption of open source and open standards, creating a culture of collaboration and efficiency
Develop a team that is seen as an engineering role model
Requirements:
10+ years experience and deep expertise as a hands-on technical leader working on complex systems in a large organization, structuring, establishing, and leading multiple product-centric engineering teams
8+ years experience driving software architecture, data architecture, AI strategy and delivery transformation through Agile practice and process, with a focus of establishing Continuous Delivery culture and process
8+ years experience and expertise in Big Data platforms and Data streaming frameworks
5+ years experience and strong expertise in Big Data & AI technologies (Spark, Hadoop, Hive, Impala, Kafka, Scala, Cloudera, Gen AI, Prompt Engineering, Agentic AI)
5+ years experience and expertise in Cloud platforms and associated Developer Toolchains, DevOps models, and best practices
5+ years of hands-on AI/ML development experience, including at least 2 years in technical leadership or team lead capacity
Proven track record of building and deploying AI applications, preferably in finance, Trade and Working Capital Finance or related industries
Experience with data governance, data standardization, and metadata management frameworks
Strong SQL and NoSQL experience (Oracle, MongoDB, PostgreSQL) for data extraction, reconciliation, and transformation
Advanced proficiency in Python and AI/ML techniques
Experience with prompt engineering, fine-tuning, and deploying LLMs in production environments
Experience with agentic AI orchestration frameworks and multi-agent systems
Strong software engineering skills: version control, CI/CD, testing, and code optimization
Familiarity with cloud platforms (AWS, GCP, Azure) and containerization (Docker, Kubernetes)
Ability to design scalable APIs and backend systems
Exceptional communicator who loves working with people, confident communicating at all levels from an individual team to the entire enterprise
Highly credible hands-on engineer, confident to deep dive into a product and codebase and offer detailed, constructive analysis and feedback
Well-developed technical written communication skills and able to effectively use internal social media platforms to communicate across the group
What we offer:
medical, dental & vision coverage
401(k)
life insurance
accident and disability insurance
wellness programs
paid time off packages (vacation, sick leave, and holidays)
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