Golang Software Engineering Lead - GenAI platforms - Senior Vice President

About the Role 

We're seeking an exceptional Golang Software Engineering Lead - GenAI platforms to drive the backend technical vision and full-stack execution of our enterprise GenAI platform serving 180,000+ Citi employees globally. This is a senior technical leadership role for someone who wants to architect scalable, high-performance AI systems at the intersection of modern cloud-native development and cutting-edge AI—combining hands-on engineering excellence with strategic technical leadership. 

You'll work with cutting-edge AI infrastructure including Claude, Gemini, and proprietary Citi models running on OpenShift/Kubernetes, building the next generation of AI-powered backend services and microservices that transform how employees interact with enterprise AI systems. 

About Our Team 

Our team operates like a research-driven startup within Citi, rapidly innovating on AI user experiences while maintaining enterprise-grade reliability, security, and compliance. We build and operate Citi Stylus Workspaces and other mission-critical GenAI platforms that demand exceptional scalability, performance, and reliability at global scale. 

Our platforms integrate cutting-edge AI models to provide secure, compliant, and powerful AI capabilities across the organization. Our microservices architecture is built with Go and React, deployed on OpenShift/Kubernetes, and incorporates sophisticated document understanding, agentic capabilities, and integration with numerous internal systems. 

What You'll Do 

Architecture & Development 

• Design, develop, and maintain core components of our production GenAI platform 

• Architect new systems and services that scale to enterprise requirements (180,000+ users) 

• Implement complex features across the entire stack, from backend services to frontend interfaces 

• Design and implement scalable microservices architecture for complex GenAI applications 

• Build sophisticated document processing and transformation pipelines 

• Optimize system performance, particularly for AI-related operations and high-throughput scenarios 

• Collaborate with AI researchers to implement state-of-the-art techniques 

• Develop real-time streaming architectures for AI responses using WebSockets and Server-Sent Events 

• Implement advanced caching strategies and distributed system patterns 

AI/ML Engineering 

• Build practical LLM-based applications with production-grade reliability 

• Implement prompt engineering techniques and patterns for enterprise use cases 

• Architect vector database solutions and semantic search capabilities 

• Design streaming architectures for AI responses and real-time collaboration 

• Integrate multiple LLM providers (Claude, Gemini, proprietary models) 

• Develop agentic capabilities and multi-agent system orchestration 

• Optimize AI inference performance and cost efficiency 

DevOps & Production 

• Design and implement observability solutions for AI-specific metrics and general system health 

• Create and maintain deployment pipelines and configuration for multiple environments 

• Build comprehensive CI/CD pipelines using GitOps workflows 

• Participate in production support rotation and incident response 

• Lead production incident response, root cause analysis, and blameless postmortem processes 

• Analyze and resolve complex production issues across the stack 

• Implement monitoring, error tracking, and alerting for production applications 

• Optimize build processes and deployment strategies for performance 

Cloud & Infrastructure 

• Design and implement Kubernetes/OpenShift deployment patterns and Helm charts 

• Architect service mesh implementations (Istio) for microservices communication 

• Implement infrastructure-as-code and GitOps workflows 

• Design network architecture for distributed systems 

• Ensure security best practices including OAuth/JWT, Vault integration, and document classification 

• Build container-based deployment strategies with high availability 

Leadership & Collaboration 

• Define technical vision and roadmap for GenAI platform backend excellence and full-stack capabilities 

• Set technical vision and drive architectural direction across multiple services and teams 

• Provide technical mentorship to engineering teams and develop technical talent 

• Lead architectural discussions and make strategic technical decisions 

• Partner with engineering, security, and business leaders to align technology strategy with organizational objectives 

• Drive engineering excellence through code reviews and best practice implementation 

• Represent the engineering organization in cross-functional leadership forums 

• Lead cross-functional collaboration with product managers, AI researchers, and frontend engineers 

• Build and lead high-performing engineering teams 

What You Bring 

Core Technical Expertise (Must-Have) 

Programming & Software Design 

• Expert-level Go programming (5+ years) with deep understanding of concurrency patterns 

• Proficiency with TypeScript/JavaScript and React (3+ years) for full-stack development 

• Strong understanding of clean architecture, SOLID principles, and design patterns 

• Experience with concurrent and parallel programming 

• Comfort with both statically and dynamically typed languages 

• Advanced knowledge of microservices architecture and API design 

• Deep understanding of RESTful APIs, gRPC, and real-time communication protocols 

Cloud & Infrastructure 

• Deep understanding of Kubernetes/OpenShift architecture and deployment patterns 

• Experience with service mesh implementations (Istio preferred) 

• Knowledge of infrastructure-as-code and GitOps workflows 

• Understanding of network architecture for distributed systems 

• Experience with containerization (Docker) and orchestration at scale 

• Proficiency with Helm charts and Kubernetes operators 

AI/ML Engineering 

• Practical experience implementing LLM-based applications in production environments 

• Knowledge of prompt engineering techniques and patterns 

• Understanding of vector databases and semantic search 

• Experience with streaming architectures for AI responses 

• Familiarity with AI model integration, fine-tuning, and optimization 

• Understanding of RAG (Retrieval-Augmented Generation) patterns 

Data & Systems 

• Experience with document processing and transformation pipelines 

• Knowledge of NoSQL databases, particularly MongoDB 

• Understanding of caching strategies and implementations (Redis) 

• Experience with high-throughput, low-latency distributed systems 

• Knowledge of S3-compatible object storage and data management 

• Understanding of data consistency patterns in distributed systems 

DevOps & Reliability 

• Strong understanding of observability (metrics, traces, logs) 

• Experience with CI/CD pipelines and automated testing 

• Knowledge of performance testing and optimization techniques 

• Experience with production incident management and resolution 

• Understanding of SRE principles and practices 

• Experience with monitoring tools (Prometheus, Grafana, ELK stack) 

Security & Compliance 

• Knowledge of OAuth/JWT authentication and authorization patterns 

• Experience with secrets management (Vault) 

• Understanding of security best practices for enterprise applications 

• Familiarity with compliance requirements in regulated industries 

Professional Experience 

• 15+ years of overall software development experience 

• 5+ years in technical leadership positions 

• 5+ years working with cloud-native architectures 

• 3+ years practical experience with AI/ML systems in production 

• Experience leading teams building enterprise-scale systems (10,000+ users) 

• Track record of successfully delivering complex technical projects at organization-wide scale 

• Experience building and leading high-performing engineering teams 

• History of mentoring and developing engineering talent 

• Experience operating in regulated industries (finance, healthcare, government) 

Nice to Have 

• Experience architecting and scaling backend systems for enterprise environments 

• Knowledge of micro-frontend architecture and module federation 

• Understanding of GraphQL and real-time data synchronization 

• Experience with AI/ML interface patterns and prompt engineering UX 

• Knowledge of event-driven architectures and message queuing systems 

• Experience with performance optimization and load testing at scale 

• Understanding of chaos engineering and resilience testing 

• Familiarity with multiple programming languages and paradigms 

Who You Are 

Beyond technical skills, you are: 

• Innovative problem solver who transforms complex technical challenges into elegant, scalable solutions 

• Passionate about AI-powered systems and leveraging AI to revolutionize enterprise applications 

• Hands-on technical leader comfortable diving deep into technical details while maintaining strategic perspective 

• Self-driven with ability to work in a fast-paced, research-oriented environment 

• Strong problem-solver with a systematic approach to complex challenges 

• Excellent communicator able to articulate complex technical concepts to diverse audiences 

• Collaborative with experience working across teams (engineering, design, product, business) 

• Curious about emerging technologies with commitment to staying current 

• Pragmatic with ability to balance ideal solutions with practical constraints and timelines 

• Comfortable with ambiguity and ability to make progress with incomplete information 

• Quality-focused with strong attention to detail and commitment to engineering excellence 

Why Join Us? 

• Cutting-Edge Technology: Work with the latest AI/ML infrastructure, modern backend frameworks, and emerging cloud-native technologies 

• Enterprise Scale: Build systems serving users globally with real business impact 

• Innovation Culture: Research-driven environment encouraging experimentation and rapid prototyping 

• Technical Excellence: Collaborate with world-class engineers and AI researchers 

• Career Growth: SVP-level technical leadership role with visibility to senior leadership 

• Meaningful Work: Build backend systems powering AI transformation across a global financial institution 

Work Environment 

We embrace a hybrid work model with a mix of in-office and remote work. We value innovation, technical excellence, and operational discipline. We operate with agile methodologies adapted to our specific needs, with two-week sprints, regular releases, and continuous improvement cycles. 

Education 

Bachelor's degree in Computer Science, Software Engineering, or related technical field, or equivalent practical experience 

Technical Environment 

• Backend: Go microservices with clean architecture patterns 

• Frontend: React 19+ with TypeScript, modern state management (Zustand), TanStack Query 

• Infrastructure: OpenShift/Kubernetes with Helm deployments, Istio service mesh 

• Data Storage: MongoDB, Redis, S3-compatible object storage 

• APIs: REST, gRPC, WebSockets, Server-Sent Events 

• AI/ML: Integration with multiple LLM providers (Claude, Gemini, proprietary models), vector search, prompt engineering 

• Security: OAuth/JWT, Vault, document classification 

• Testing: Comprehensive testing strategies (unit, integration, E2E) 

• Build Tools: Modern CI/CD pipelines, GitOps workflows 

• Observability: Metrics, traces, logs, monitoring and alerting 

• Performance: High-throughput, low-latency distributed systems optimization 

Ready to Apply? 

If you're passionate about building scalable, intelligent backend systems at the intersection of AI and modern cloud-native development, and want to shape the future of enterprise AI platforms at global scale, we'd love to hear from you. 

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