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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## Job Family Group:
Technology
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## Job Family:
Applications Development
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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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