Generative AI engineer for enterprise operations

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.

• Lead the hands-on development of sophisticated Generative AI applications, LLM-powered solutions, and intricate agentic frameworks primarily using Python. Your code will be clean, performant, scalable, and deployed directly into commercial production environments, solving real business problems.
• Design and implement intelligent agents capable of understanding, reasoning, and orchestrating complex workflows to automate critical enterprise business processes, driving efficiency and reducing operational risk at scale.
• Demonstrate deep comfort and expertise with container technologies, particularly deploying and managing applications within OpenShift environments.
• Contribute significantly to the technical strategy and roadmap for Generative AI adoption, influencing architectural decisions and technology choices across our product portfolio, ensuring all solutions are production-ready.
• Instill and uphold rigorous software engineering best practices, including robust testing, code reviews, documentation, and continuous integration/delivery, ensuring the highest quality for our mission-critical systems running in production.
• Stay at the bleeding edge of Generative AI, actively exploring new models, techniques, and frameworks. Contribute to both applied engineering and research initiatives within the domain. You will have access to state-of-the-art AI-assisted development tools like Devin and Copilot to amplify your productivity and creativity.
• Act as a technical leader and mentor to junior engineers, fostering a culture of knowledge sharing and continuous improvement. Collaborate closely with cross-functional teams, product managers, and stakeholders to deliver impactful solutions.
• Thrive in an agile, fast-paced environment, prioritizing rapid delivery, iterative development, and adaptability. Focus on delivering measurable business value and learning quickly from prototypes and deployments, always with a path to production in mind.
• Design and implement robust guardrails and ethical considerations into AI solutions, proactively assessing and mitigating risks in line with organizational and regulatory standards.

• Professional software engineering experience, demonstrating a strong track record of designing, building, and delivering scalable enterprise-grade solutions in commercial production environments, not just proofs-of-concept.
• Expert-level proficiency in Python is a must-have, with a deep understanding of its ecosystem for AI/ML development, data engineering, and backend services. Full-stack development experience is a distinct advantage.
• Extensive hands-on experience with Generative AI concepts, Large Language Models (LLMs), transformer architectures, RAG, and advanced agentic frameworks (e.g., LangChain, LangGraph, Google ADK. Optionally AutoGen, CrewAI, LlamaIndex, Semantic Kernel).
• 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.
• Будет плюсом: 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

• Contribute to critical, high-visibility projects that are transforming a global enterprise, working on firm-wide initiatives that directly influence our operational future.
• 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.
• A culture of continuous learning, mentorship, and opportunities to lead and innovate. Benefit from extensive learning resources including Udemy for Business and Pluralsight.
• Join a highly skilled, passionate team that values collaboration, intellectual curiosity, and shared success.
• Embrace a hybrid working model, balancing productive in-office collaboration (3 days) with the flexibility of working from home (up to 2 days).
• Build solutions that operate at a massive scale, impacting users and operations worldwide.