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At Citi, we are pioneering the future of enterprise operations through innovative technology. Our COO-Technology Engineering and Architecture capability is at the forefront, responsible for architecting best-in-class solutions, driving end-to-end transformation, and integrating cutting-edge Generative AI solutions to unlock unparalleled efficiency, automation, and risk reduction across our global operations. We are seeking an exceptional Staff Generative AI Engineer to join our team. This is a critical, deeply hands-on role for a seasoned software engineer with a profound passion for Generative AI, Large Language Models (LLMs), and agentic frameworks. You will be instrumental in designing, building, and deploying real-world, commercial production systems, not just proofs-of-concept.
Job Responsibility:
Architect & Build Production Systems: Lead the hands-on development of sophisticated Generative AI applications, LLM-powered solutions, and intricate agentic frameworks primarily using Python
Pioneer Automation with Agents: Design and implement intelligent agents capable of understanding, reasoning, and orchestrating complex workflows to automate critical enterprise business processes
Master Containerized Deployments: Demonstrate deep comfort and expertise with container technologies, particularly deploying and managing applications within OpenShift environments
Drive Technical Direction & Ownership: Contribute significantly to the technical strategy and roadmap for Generative AI adoption
Champion Engineering Excellence: Instill and uphold rigorous software engineering best practices
Innovate & Research: Stay at the bleeding edge of Generative AI, actively exploring new models, techniques, and frameworks
Mentor & Collaborate: Act as a technical leader and mentor to junior engineers
Iterate & Deliver: Thrive in an agile, fast-paced environment, prioritizing rapid delivery, iterative development, and adaptability
Ensure Responsible AI: Design and implement robust guardrails and ethical considerations into AI solutions
Requirements:
Proven professional software engineering experience, designing, building, and delivering scalable enterprise-grade solutions in commercial production environments
Expert-level proficiency in Python
Extensive hands-on experience with Generative AI concepts, Large Language Models (LLMs), transformer architectures, RAG, and advanced agentic frameworks
Deep comfort and practical experience with containers and orchestration technologies, specifically OpenShift
Demonstrated ability to architect, develop, and deploy highly performant, large-scale AI/ML systems into production environments
Strong understanding of modern software development principles, clean code practices, data structures, algorithms, and distributed systems
Proficiency with Relational (preferably, PostgreSQL) and Vector (preferably, pgvector) databases
Nice to have:
Proficiency in additional programming languages such as Java, JavaScript/TypeScript, or Golang
Experience with specific frameworks like Spring (AI, Boot), N8N, or Flask
Familiarity with messaging and integration platforms such as Kafka or JMS/MQ
Experience with UI development using modern frameworks like React JS or StreamLit for interactive AI applications
Practical experience in model risk management, developing AI guardrails, and establishing end-user adoption pathways for Generative AI solutions
A proven track record of contributing to open-source projects or publishing relevant research in AI/ML
What we offer:
Unprecedented Impact & Visibility: Contribute to critical, high-visibility projects that are transforming a global enterprise
Cutting-Edge Technology: Work with the latest Generative AI models, agentic frameworks, and cloud-native technologies, enhanced by access to AI-assisted development tools like Devin and Copilot
Growth & Development: A culture of continuous learning, mentorship, and opportunities to lead and innovate
Benefit from extensive learning resources including Udemy for Business and Pluralsight
Collaborative Environment: Join a highly skilled, passionate team that values collaboration, intellectual curiosity, and shared success
Flexible Work Environment: Embrace a hybrid working model, balancing productive in-office collaboration (3 days) with the flexibility of working from home (up to 2 days)
Global Scale: Build solutions that operate at a massive scale, impacting users and operations worldwide