Lead Backend Engineer - Golang (Product Engineering)

ABOUT OOLIO:

Oolio is a leading B2B SaaS platform transforming how hospitality venues operate and grow. Trusted by more than 22,000 venues, we power mission-critical POS, payments, online ordering, kiosks, loyalty, kitchen management, and real-time insights — all within one connected ecosystem.

We are building the operating system for modern hospitality — simplifying complex operations, accelerating service, and unlocking smarter, data-driven decisions. Built by hospitality professionals with decades of industry experience, we understand the realities of every shift, every service rush, and every guest interaction. From cafés and quick-service restaurants to pubs, multi-site groups, and stadiums, Oolio enables venues to operate seamlessly at scale. With next-business-day settlements, powerful third-party integrations, and 24/7 real human support, we go beyond software — we become long-term partners in growth.

As a rapidly scaling product-led organisation, we’re shaping the future of hospitality technology.

We build the technology backbone that powers modern hospitality businesses to perform, compete, and thrive at scale.

JOB DESCRIPTION:

At Oolio, Lead Backend Engineer – Golang are hands-on technical leaders who design, build, and operate scalable, reliable, and high-performance backend systems. You will take ownership across the complete backend engineering lifecycle — from architecture and system design through development, testing, deployment, observability, and production reliability.

The role requires deep expertise in Golang, microservices, distributed systems, APIs, event-driven architectures, cloud-native technologies, and system performance. As AI continues to transform software engineering, you will also be encouraged to leverage AI-powered development tools, automation, and emerging AI capabilities to improve engineering productivity, accelerate delivery, enhance code quality, and solve real-world engineering problems.

The primary focus of this role is backend engineering and technical leadership, with AI serving as an additional capability rather than the core domain. You will work closely with Product, Design, Platform, and Engineering teams to build customer-facing products and the backend capabilities that support Oolio's growing global platform.

RESPONSIBILITIES:

• Own end-to-end development of backend services—from architecture and design to deployment, observability, and production reliability.
• Design and implement scalable, distributed microservices using Golang with strong emphasis on performance, concurrency, and maintainability.
• Architect and evolve event-driven systems using async messaging, queues, pub/sub, and streaming patterns to support high-scale, low-latency applications.
• Build and optimize RESTful and/or gRPC APIs that power web, mobile, and third-party integrations.
• Contribute across the stack when required, collaborating with React and Node.js services to deliver cohesive product features.
• Develop cloud-native services deployed on AWS, leveraging Kubernetes and Docker for containerized infrastructure.
• Optimize application performance, throughput, scalability, and reliability as product usage and customer scale increase.
• Implement strong testing strategies including unit, integration, contract, and performance testing.
• Drive observability best practices including structured logging, monitoring, metrics, tracing, and alerting.
• Participate in code reviews and actively contribute to improving engineering standards and best practices.
• Troubleshoot complex production issues, perform root cause analysis, and implement long-term systemic fixes.
• Design and implement AI-powered engineering workflows that improve software delivery velocity and engineering productivity.
• Develop agentic workflows capable of interacting with code repositories, ticketing systems, deployment pipelines, and engineering platforms.
• Evaluate and integrate modern AI technologies, frameworks, and tooling into the engineering ecosystem.
• Identify bottlenecks across the SDLC and implement AI-driven solutions that improve efficiency, quality, and developer experience.
• Drive adoption of AI-native software engineering practices and continuously improve engineering effectiveness across teams.

REQUIREMENTS:

Role: Lead Backend Engineer (Product Engineering) – final role will depend on candidate experience, credentials and interview outcomes

Experience: 8 – 18 Years

Education: Preferred – B.Tech/B.E/M.Tech/M.E/MCA/M.S

Technology Stack:

(A) Core Engineering:

Golang, Microservices, Distributed Systems, Event-Driven Architecture, REST APIs, gRPC, System Design (HLD/LLD), Performance Optimization, Testing Frameworks, AI-Powered Development Tooling

(B) Good/Nice to Have:

ReactJS, NodeJS, GraphQL

OTHER REQUIREMENTS:

• Strong hands-on experience building production-grade backend systems in SaaS or product-based organisations.
• Deep expertise in Golang, including concurrency patterns, goroutines, channels, memory management, profiling, and performance optimization.
• Proven experience designing and operating scalable microservices and distributed systems.
• Strong understanding of API design, asynchronous processing, event-driven architectures, and system reliability principles.
• Experience with PostgreSQL, DynamoDB, or similar databases, including schema design, indexing, and query optimization.
• Hands-on experience with AWS, Kubernetes, Docker, and cloud-native application development.
• Strong experience implementing and improving CI/CD pipelines and modern software delivery practices.
• Strong understanding of observability, monitoring, logging, tracing, fault tolerance, and production reliability.
• Experience troubleshooting complex production issues, conducting root cause analysis, and implementing long-term improvements.
• Experience working in high-scale or high-transaction environments is highly desirable.
• Practical experience leveraging AI technologies to improve software engineering productivity and software delivery outcomes.
• Experience building or integrating AI-powered workflows across development, testing, documentation, deployment, observability, or operational processes.
• Passion for exploring emerging AI capabilities and applying them pragmatically to real-world engineering challenges.
• Ability to balance traditional software engineering principles with AI-native development practices.