Golang Software Engineering Lead - GenAI platforms - Senior Vice President at Citi

Pune, maharashtra, India -

Full Time

Start Date

Immediate

Expiry Date

16 Oct, 26

Salary

0.0

Posted On

18 Jul, 26

Experience

10 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Golang, React, TypeScript, Kubernetes, OpenShift, LLM, Prompt Engineering, Vector Databases, Microservices, Istio, gRPC, RAG, MongoDB, Redis, CI/CD, GitOps

Industry

Financial Services

Description

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. ------------------------------------------------------ Job Family Group: Technology ------------------------------------------------------ Job Family: Applications Development ------------------------------------------------------ Time Type: Full time ------------------------------------------------------ Most Relevant Skills Please see the requirements listed above. ------------------------------------------------------ Other Relevant Skills For complementary skills, please see above and/or contact the recruiter. ------------------------------------------------------ Citi is an equal opportunity employer, and qualified candidates will receive consideration without regard to their race, color, religion, sex, sexual orientation, gender identity, national origin, disability, status as a protected veteran, or any other characteristic protected by law. If you are a person with a disability and need a reasonable accommodation to use our search tools and/or apply for a career opportunity review Accessibility at Citi. View Citi’s EEO Policy Statement and the Know Your Rights poster.

Responsibilities

Lead the technical vision and backend execution of an enterprise GenAI platform serving over 180,000 employees. Architect scalable microservices and AI-powered backend systems while mentoring engineering teams and collaborating with AI researchers.