Golang Software Engineering Lead - GenAI platforms - Senior Vice President

Citi · Pune · 5+ yrs experience · Posted 2026-07-18

Tech stack: Docker, Go, Golang, GraphQL, JavaScript, Kubernetes, MongoDB, React, Redis, TypeScript

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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.
Responsibilities: - 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
Qualifications: - 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 with service mesh implementations (Istio preferred)
- of infrastructure-as-code and GitOps workflows
- Understanding of network architecture for distributed systems 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 of prompt engineering techniques and patterns
- Understanding of vector databases and semantic search with streaming architectures for AI responses
- Familiarity with AI model integration, fine-tuning, and optimization
- Understanding of RAG (Retrieval-Augmented Generation) patterns
- Data & Systems with document processing and transformation pipelines of NoSQL databases, particularly MongoDB
- Understanding of caching strategies and implementations (Redis)
- with high-throughput, low-latency distributed systems 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)
- with CI/CD pipelines and automated testing of performance testing and optimization techniques with production incident management and resolution
- Understanding of SRE principles and practices with monitoring tools (Prometheus, Grafana, ELK stack)
- Security & Compliance of OAuth/JWT authentication and authorization patterns 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 leading teams building enterprise-scale systems (10,000+ users)
- Track record of successfully delivering complex technical projects at organization-wide scale
- building and leading high-performing engineering teams
- History of mentoring and developing engineering talent operating in regulated industries (finance, healthcare, government)
- Nice to Have architecting and scaling backend systems for enterprise environments of micro-frontend architecture and module federation Understanding of GraphQL and real-time data synchronization with AI/ML interface patterns and prompt engineering UX of event-driven architectures and message queuing systems 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.
- Bachelor's degree in Computer Science Software Engineering, or related technical field, or e

Qualifications

- 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 with service mesh implementations (Istio preferred)
- of infrastructure-as-code and GitOps workflows
- Understanding of network architecture for distributed systems 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 of prompt engineering techniques and patterns
- Understanding of vector databases and semantic search with streaming architectures for AI responses
- Familiarity with AI model integration, fine-tuning, and optimization
- Understanding of RAG (Retrieval-Augmented Generation) patterns
- Data & Systems with document processing and transformation pipelines of NoSQL databases, particularly MongoDB
- Understanding of caching strategies and implementations (Redis)
- with high-throughput, low-latency distributed systems 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)
- with CI/CD pipelines and automated testing of performance testing and optimization techniques with production incident management and resolution
- Understanding of SRE principles and practices with monitoring tools (Prometheus, Grafana, ELK stack)
- Security & Compliance of OAuth/JWT authentication and authorization patterns 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 leading teams building enterprise-scale systems (10,000+ users)
- Track record of successfully delivering complex technical projects at organization-wide scale
- building and leading high-performing engineering teams
- History of mentoring and developing engineering talent operating in regulated industries (finance, healthcare, government)
- Nice to Have architecting and scaling backend systems for enterprise environments of micro-frontend architecture and module federation
- Understanding of GraphQL and real-time data synchronization with AI/ML interface patterns and prompt engineering UX of event-driven architectures and message queuing systems 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.
- Bachelor's degree in Computer Science Software Engineering, or related technical field, or e

Responsibilities

- 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

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