Golang Software Engineering Lead - GenAI platforms - Senior Vice President
Citi
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Job summary
Citi is seeking a Golang Software Engineering Lead for its GenAI platforms to drive backend architecture and full-stack delivery for an enterprise-scale solution used by 180,000+ Citi employees globally.
You will design scalable microservices on OpenShift/Kubernetes, integrate multiple LLM providers, and lead a team to build high-performance AI-powered backend services with strong reliability and security.
Qualifications
- Fifteen plus years in software development with leadership experience.
- Five plus years in technical leadership, cloud-native architectures.
- Three plus years with AI/ML systems in production.
- Experience delivering enterprise-scale systems serving thousands of users.
Responsibilities
- Design, develop, and maintain core components of the GenAI platform.
- Lead architecture and technical direction across backend and full-stack.
- Mentor engineers and drive engineering excellence through reviews.
- Collaborate with AI researchers to implement state-of-the-art techniques.
- Design streaming architectures and real-time AI response systems.
Skills
Education
Tools
Job description
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.
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.
- 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
- 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
- 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
- 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
- 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
- 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
- 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
- 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
- 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
- Strong understanding of observability (metrics, traces, logs)
- Experience with CI/CD pipelines and automated testing
- Knowledge of performance testing and optimization techniquesExperience with production incident management and resolution
- Understanding of SRE principles and practices
- Experience with monitoring tools (Prometheus, Grafana, ELK stack)
- 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
- 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)
- 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
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
- 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
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.
Bachelor's degree in Computer Science, Software Engineering, or related technical field, or equivalent practical experience
- 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
Technology
Applications Development
Full time
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