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

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

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

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

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Design and implement scalable microservices architecture for complex GenAI applications

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Build sophisticated document processing and transformation pipelines

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

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

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

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Implement advanced caching strategies and distributed system patterns

AI/ML Engineering

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Build practical LLM-based applications with production-grade reliability

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Implement prompt engineering techniques and patterns for enterprise use cases

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Architect vector database solutions and semantic search capabilities

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Design streaming architectures for AI responses and real-time collaboration

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

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Develop agentic capabilities and multi-agent system orchestration

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Optimize AI inference performance and cost efficiency

DevOps & Production

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

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Create and maintain deployment pipelines and configuration for multiple environments

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Build comprehensive CI/CD pipelines using   GitOps   workflows

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Participate in production support rotation and incident response

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

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Analyze and resolve complex production issues across the stack

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Implement monitoring, error tracking, and alerting for production applications

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Optimize build processes and deployment strategies for performance

Cloud & Infrastructure

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Design and implement Kubernetes/OpenShift deployment patterns and Helm charts

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Architect service mesh implementations (Istio) for microservices communication

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Implement infrastructure-as-code and   GitOps   workflows

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Design network architecture for distributed systems

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

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Build container-based deployment strategies with high availability

Leadership & Collaboration

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

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

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Provide technical mentorship to engineering teams and develop technical talent

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Lead architectural discussions and make strategic technical decisions

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

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Drive engineering excellence through code reviews and best practice implementation

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Represent the engineering organization in cross-functional leadership forums

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

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Build and lead high-performing engineering teams

What You Bring

Core Technical Expertise (Must-Have)

Programming & Software Design

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

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

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

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Experience with concurrent and parallel programming

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Comfort with both statically and dynamically typed languages

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Advanced knowledge of microservices architecture and API design

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

Cloud & Infrastructure

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Deep understanding of Kubernetes/OpenShift architecture   and deployment patterns

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Experience with service mesh implementations (Istio preferred)

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Knowledge of infrastructure-as-code and   GitOps   workflows

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Understanding of network architecture for distributed systems

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Experience with containerization (Docker) and orchestration at scale

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Proficiency with Helm charts and Kubernetes operators

AI/ML Engineering

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Practical experience implementing LLM-based applications   in production environments

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Knowledge of prompt engineering techniques and patterns

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Understanding of vector databases and semantic search

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Experience with streaming architectures for AI responses

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

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Understanding of RAG (Retrieval-Augmented Generation) patterns

Data & Systems

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Experience with document processing and transformation pipelines

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Knowledge of NoSQL databases, particularly MongoDB

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Understanding of caching strategies and implementations (Redis)

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Experience with high-throughput, low-latency distributed systems

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Knowledge of S3-compatible object storage and data management

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Understanding of data consistency patterns in distributed systems

DevOps & Reliability

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Strong understanding of observability   (metrics, traces, logs)

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Experience with CI/CD pipelines and automated testing

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Knowledge of performance testing and optimization techniques

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Experience with production incident management and resolution

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Understanding of SRE principles and practices

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

Security & Compliance

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Knowledge of OAuth/JWT authentication and authorization patterns

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Experience with secrets management (Vault)

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Understanding of security best practices for enterprise applications

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Familiarity with compliance requirements in regulated industries

Professional Experience

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15+ years of overall software development experience

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5+ years in technical leadership positions

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5+ years working with cloud-native architectures

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

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

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

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Experience building and leading high-performing engineering teams

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History of mentoring and developing engineering talent

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