Citi
Pune Maharashtra India
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.
Technology
Applications Development
Full time
Please see the requirements listed above.
For complementary skills, please see above and/or contact the recruiter.
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