• Partner directly with enterprise customers to understand business goals, operational challenges, and AI transformation priorities. • Collaborate with sales teams throughout the customer lifecycle, from discovery and demonstrations to deployment and adoption. • Conduct technical discovery sessions, solution workshops, and executive presentations. • Design practical AI-powered solutions that address real business challenges. • Translate customer requirements into scalable, production-ready solution architectures. • Build customer-specific AI use cases, workflows, and business scenarios. • Develop, validate, and deliver proof of concepts, pilot programs, and production-ready solutions. • Configure, optimize, and operationalize AI solutions within customer environments. • Lead enterprise AI implementations from discovery through deployment and operational adoption. • Facilitate technical workshops, implementation planning, onboarding, testing, and rollout activities. • Coordinate cross-functional teams to ensure successful delivery and customer adoption. • Map customer business processes, data flows, and operational requirements into AI-enabled workflows. • Support data integrations, solution configuration, and workflow optimization. • Identify opportunities to improve business processes through AI, automation, analytics, and data-driven decision-making. • Troubleshoot technical issues, workflow challenges, and adoption barriers. • Drive customers from pilot initiatives to enterprise-scale AI deployments. • Balance technical constraints, business priorities, and customer objectives to deliver measurable outcomes. • Contribute to reusable implementation frameworks, playbooks, best practices, and deployment methodologies. • Provide customer insights that influence product strategy and future AI solution development. • Promote long-term customer success through continuous improvement and knowledge sharing.

• Partner directly with enterprise customers to understand business goals, operational challenges, and AI transformation priorities. • Collaborate with sales teams throughout the customer lifecycle, from discovery and demonstrations to deployment and adoption. • Conduct technical discovery sessions, solution workshops, and executive presentations. • Design practical AI-powered solutions that address real business challenges. • Translate customer requirements into scalable, production-ready solution architectures. • Build customer-specific AI use cases, workflows, and business scenarios. • Develop, validate, and deliver proof of concepts, pilot programs, and production-ready solutions. • Configure, optimize, and operationalize AI solutions within customer environments. • Lead enterprise AI implementations from discovery through deployment and operational adoption. • Facilitate technical workshops, implementation planning, onboarding, testing, and rollout activities. • Coordinate cross-functional teams to ensure successful delivery and customer adoption. • Map customer business processes, data flows, and operational requirements into AI-enabled workflows. • Support data integrations, solution configuration, and workflow optimization. • Identify opportunities to improve business processes through AI, automation, analytics, and data-driven decision-making. • Troubleshoot technical issues, workflow challenges, and adoption barriers. • Drive customers from pilot initiatives to enterprise-scale AI deployments. • Balance technical constraints, business priorities, and customer objectives to deliver measurable outcomes. • Contribute to reusable implementation frameworks, playbooks, best practices, and deployment methodologies. • Provide customer insights that influence product strategy and future AI solution development. • Promote long-term customer success through continuous improvement and knowledge sharing.

• Partner directly with enterprise customers to understand business goals, operational challenges, and AI transformation priorities. • Collaborate with sales teams throughout the customer lifecycle, from discovery and demonstrations to deployment and adoption. • Conduct technical discovery sessions, solution workshops, and executive presentations. • Design practical AI-powered solutions that address real business challenges. • Translate customer requirements into scalable, production-ready solution architectures. • Build customer-specific AI use cases, workflows, and business scenarios. • Develop, validate, and deliver proof of concepts, pilot programs, and production-ready solutions. • Configure, optimize, and operationalize AI solutions within customer environments. • Lead enterprise AI implementations from discovery through deployment and operational adoption. • Facilitate technical workshops, implementation planning, onboarding, testing, and rollout activities. • Coordinate cross-functional teams to ensure successful delivery and customer adoption. • Map customer business processes, data flows, and operational requirements into AI-enabled workflows. • Support data integrations, solution configuration, and workflow optimization. • Identify opportunities to improve business processes through AI, automation, analytics, and data-driven decision-making. • Troubleshoot technical issues, workflow challenges, and adoption barriers. • Drive customers from pilot initiatives to enterprise-scale AI deployments. • Balance technical constraints, business priorities, and customer objectives to deliver measurable outcomes. • Contribute to reusable implementation frameworks, playbooks, best practices, and deployment methodologies. • Provide customer insights that influence product strategy and future AI solution development. • Promote long-term customer success through continuous improvement and knowledge sharing.

Role Description We're seeking an experienced Go Engineer to join our team and contribute significantly to our payment gateway product. The ideal candidate will bring deep technical expertise, a collaborative mindset, and the ability to influence and mentor team members through knowledge and experience rather than formal authority. About the project: - Payment gateway solutions - fintech product that securely connects merchants and financial institutions to process online payments in real time. - Handles transaction routing, encryption and tokenization, fraud and risk checks, and integration with acquirers, payment aggregators, and alternative payment methods. - Supports high availability, scalability, and compliance with PCI DSS and PSD2. Tech stack: - Go - PostgreSQL/MySQL - MongoDB/Redis - Kafka - NATS - REST/gRPC - AWS - GitLab CI/CD - Prometheus - Grafana Key responsibilities: - Design and develop Go-based services for the payment gateway and related fintech systems, focusing on stability, fault tolerance, and correct handling of financial operations. - Translate business requirements into clear technical specifications and propose concrete solutions at the service and module level, including API design, data models, and integrations with external providers. - Build solutions in compliance with security requirements, including PCI DSS, proper handling of sensitive data, and secure inter-service communication. - Analyze and optimize service performance, including code profiling, concurrency handling, and efficiency of data storage and network interactions. - Participate in the architecture of microservices: service boundaries, communication patterns, load balancing, error handling, queues/streaming, and data storage approaches. - Produce maintainable, testable code with appropriate unit and integration test coverage, following team development standards. - Participate in code review as part of the development process: evaluate implementations, identify issues, and provide constructive feedback aligned with technical requirements. - Contribute to technical discussions by offering concrete, practical solutions within the current architecture and development processes. Qualifications - 3–5 years of Go development experience focused on backend systems, and around 5 years of experience working with fintech applications. - Understanding of distributed systems, microservices architecture, and API design, including REST/RPC transports. - Experience working with SQL and NoSQL databases, message brokers (Kafka, NATS), and caching systems. - Familiarity with CI/CD practices and tools, preferably GitLab. - Experience working with the AWS cloud platform. - Ability to contribute expertise and collaborate with the team on technical solutions. - Strong communication skills and the ability to explain complex technical ideas to colleagues with varying levels of technical background. - Fluency in written and spoken English and Russian. - Experience in the fintech domain. - Security-by-design mindset: ability to design solutions with security considerations built in at every stage. - Understanding of regulatory requirements in the fintech space (e.g., PCI DSS, GDPR). - Experience in performance optimization and building high-availability systems. - Experience with observability tools: logging, metrics, tracing (Prometheus, Grafana, OpenTelemetry). - Experience integrating with external payment providers, processors, or anti-fraud systems. Benefits - Opportunity to shape the future of fintech solutions within a growing company. - Collaborative, horizontal team structure that values your expertise and ideas. - Continuous learning and development opportunities to enhance your skills and career growth. - Competitive salary and benefits package. - Flexible work arrangements to support work-life balance.