The Digital S/W Engineer Sr Mgr accomplishes results through the management of professional team(s) and department(s). Responsible for Design and implementation of cutting-edge AI/ML solutions that power intelligent, multilingual digital experiences across customer-facing and operational platforms. Requires broad full-stack engineering expertise with deep specialization in AI/ML with an ability to build and optimize LLM-powered workflows, agentic AI systems, and machine learning models to enable natural language understanding, intelligent automation, and personalized self-service, bridging intelligent systems with enterprise-grade digital platforms across millions of interactions spanning multiple languages. Full management responsibility of a team, which may include management of people, budget and planning and duties such as performance evaluation.

Responsibilities:

• Accountable for executing and driving enterprise grade application design and development efforts to completion, serving as a development lead
• Proficient at operating with considerable autonomy and significantly influence the way an application is designed and developed by providing subject specific expertise and an advanced level of understanding of application programming principles.
• Participate in design discussions as a Development Lead and play the part of a key decision maker in driving design decisions.
• Partner with industry vendors that provide technology or user experience design components that support our Digital architecture and work with vendors on our implementation plans and roadmaps identifying partnership opportunities to increase our development velocity and our learnings.
• Directly impact the business by influencing strategic functional decisions through advice, counsel or provided services. This will require persuading and influencing others through strong and comprehensive communication and diplomacy skills.
• Communicate progress, anticipate bottlenecks, provide escalation management, identify, assess, track and mitigate issues/risks at multiple levels.
• Regularly review metrics and proactively seek out new and improved mechanisms for visibility ensuring your program stays aligned with organization objectives.
• Share knowledge with the team in various forums (brown bags, engineering forums etc.) and demonstrate a higher level of knowledge through industry certifications
• Integrate LLMs for conversational understanding and response generation
• Implement RAG for dynamic knowledge base integration
• Design agentic AI workflows (LangChain, LangGraph, CrewAI) for complex scenarios
• Develop multi-agent systems for handling of complaints, account opening, cross-selling, and fee reversals
• Create prompt engineering strategies for compliant and context-aware responses
• Optimize LLM costs and implement guardrails to prevent hallucinations.
• Build personalized recommendation engines with receptiveness detection to maximize relevance and engagement
• Develop learning systems that continuously adapt based on customer acceptance and rejection patterns
• Design AI models that identify opportune moments for contextual cross-sell and upsell within digital journeys
• Leverage customer interaction history and behavioral signals to deliver personalized digital experiences
• Design AI-driven digital routing logic based on intent, sentiment, urgency, customer tier, and interaction history
• Build automated self-service workflows for common digital journeys: fee reversals, rewards redemption, account management, and more
• Create intelligent complaint detection workflows - identifying indirect complaints, assessing severity, and routing to appropriate resolution paths
• Develop engagement flows for non-authenticated and prospective customer interactions
• Build real-time sentiment/urgency analysis and emotion detection
• Create adaptive dialogues adjusting to customer emotion
• Implement churn risk scoring and escalation triggers
• Appropriately assess risk when business decisions are made, demonstrating particular consideration for the firm's reputation and safeguarding Citigroup, its clients and assets, by driving compliance with applicable laws, rules and regulations, adhering to Policy, applying sound ethical judgment regarding personal behavior, conduct and business practices, and escalating, managing and reporting control issues with transparency.

Qualifications:

• 11-17 years of relevant experience in an Apps Development role or senior level experience in an Enterprise Architecture role with subject matter expertise in one or more areas with at least 3+ years of deep specialization in AI/ML, NLP, or Generative AI development
• Proven experience in successfully building, leading, and delivering complex technology projects from conception through to deployment and ongoing support
• Proven experience in leading high performance teams spread across multiple locations
• Effectively coach and give feedback to direct reports to help develop talent and support career development.
• 2+ years of experience building and operating production-grade AI systems such as digital assistants, recommendation engines, or similar intelligent platforms
• 2+ years of deep, applied experience with LLM technologies (GPT-4, Claude, Gemini, or equivalent), including prompt engineering, fine-tuning, and cost optimization in production environments
• Hands-on expertise in implementing Retrieval-Augmented Generation (RAG) pipelines and working with vector databases for knowledge-grounded AI applications
• Demonstrable experience in designing and deploying agentic AI workflows and multi-agent systems using modern frameworks
• Proficiency in NLP model development using industry-standard libraries and ML frameworks
• Expert-level Python development skills with strong command of RESTful APIs, microservices architecture, and cloud platforms
• Broad full-stack engineering experience across backend (Java, microservices) and frontend (Angular, React, or similar JavaScript frameworks), with a proven ability to design, develop, and deliver end-to-end enterprise-grade digital applications across multiple technology layers
• Experience in enterprise architecture principles, with the ability to design, govern, and integrate scalable technology solutions across complex organizational environments, bridging intelligent AI systems with enterprise-grade digital platforms
• Working knowledge of real-time data streaming technologies and databases across SQL, NoSQL, and vector paradigms
• Hands-on experience with MLOps practices and tools, including model deployment, versioning, monitoring, and lifecycle management to ensure reliable and scalable AI systems in production
• Demonstrable expertise in utilizing modern development tools and technologies across all phases of the Software Development Life Cycle (SDLC) (e.g., Devin, GitHub Co-pilot, or equivalent).
• Working knowledge and adherence to industry best practices and established software development standards.
• A strong and comprehensive understanding of Wealth Management, Retail Banking operations, CRM, various investment products, and critical back-office operations within a financial institution.
• Exceptional written and verbal communication skills, with the ability to articulate complex technical concepts and strategic objectives clearly and concisely to diverse audiences.
• Prior experience in senior stakeholder management, effectively communicating and collaborating with executive leadership and key business partners.

Education:

• Bachelor's or Master's degree in Computer Science, AI/ML, Data Science, or related field

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Job Family Group:

Technology

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Job Family:

Digital Software Engineering

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Time Type:

Full time

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Most Relevant Skills

Please see the requirements listed above.

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Other Relevant Skills

For complementary skills, please see above and/or contact the recruiter.

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