[Hiring] Senior Backend / Platform Engineer @Gramian Consulting Group

Role Description

Our client is a Big4 Consultancy group that works with leading financial institutions on AI-driven transformation, automation, advanced analytics, and financial crime prevention. Their work spans intelligent fraud detection, AML/KYC modernization, autonomous workflows, enterprise AI platforms, and the secure industrialization of AI in highly regulated environments.

We are looking for a Senior Backend / Platform Engineer to build scalable backend services and core platform components supporting production AI applications. The role focuses on:

• Microservices
• APIs
• Cloud integration
• Authentication
• Performance optimization
• Secure platform engineering across AWS and Azure environments

CONTRACT: Contractor assignment, expected October 2026 – July 2027, with potential extension

COMMITMENT: Full-time

LOCATIONS: Europe-based, preferably CEE; remote, with potential future hybrid work in Prague

PROCESS: Initial qualification followed by technical and client interviews

NOTES: Fluent English is required. Strong AWS experience is highly preferred.

Qualifications

• 5–10 years of professional backend, platform, or software engineering experience
• Strong hands-on development experience with Python and/or Node.js
• Proven experience building scalable, resilient, and secure cloud-based applications
• Strong experience designing RESTful or GraphQL APIs and microservices
• Hands-on experience with enterprise authentication, authorization, and RBAC
• Professional experience integrating applications with cloud-hosted services, APIs, and data platforms
• Strong development practices including Git, CI/CD, automated testing, and code review
• Fluent professional English

Responsibilities

• Design and build highly scalable, resilient, and secure microservices and backend APIs
• Develop RESTful and GraphQL services for production-grade applications
• Integrate business databases, third-party services, and legacy internal platforms with AI systems
• Optimize backend latency, throughput, and resource allocation for real-time AI workloads
• Implement enterprise-grade authentication, authorization, RBAC, and rate limiting
• Build secure service-to-service integrations across cloud environments
• Establish clean coding standards and maintain strong engineering quality
• Write comprehensive integration tests and participate in code reviews
• Collaborate with AI engineers to deploy models and services in unified containerized environments
• Apply Git, CI/CD, testing, and cloud engineering best practices throughout delivery