• Designing, developing, and maintaining scalable backend solutions • Implementing and optimizing business processes using Camunda 8 • Collaborating with cross-functional teams to deliver high-quality software • Participating in technical design discussions and contributing to software architecture decisions • Writing clean, maintainable, and well-documented code • Developing and maintaining automated tests to ensure software quality • Actively participating in code reviews and quality assurance initiatives • Refining user stories and technical requirements with the development team • Mentoring and coaching junior developers • Preparing technical documentation and presenting new features and technical solutions

• Participate in the design, development, and maintenance of innovative enterprise applications. • Collaborate with business stakeholders and technical teams to analyze requirements and define technical solutions. • Mentor junior developers and contribute to a strong engineering culture. • Design and develop new application modules and microservices-based solutions. • Develop and maintain backend and frontend components using modern technologies and frameworks. • Create and execute test cases, ensuring software quality and reliability. • Participate in CI/CD processes, deployments, and production support activities. • Diagnose and resolve incidents, performance bottlenecks, and application issues. • Contribute to architecture discussions, technical decisions, and best engineering practices. • Use repositories, DevOps pipelines, and software development tools efficiently. • Promote clean code, maintainability, observability, and security best practices. • Leverage AI-assisted development tools throughout the SDLC to improve productivity, quality, and delivery speed. • Collaborate in the adoption of AI engineering best practices, governance, and secure usage of AI tools in enterprise environments.

• Design and evolve TeamBuilder's platform architecture across application, data, analytics, and AI layers • Establish architectural standards and engineering best practices for scalable, secure, and maintainable systems • Lead development of scalable SaaS products and services using C#, .NET, ASP.NET Core, SQL, Redis, and related Microsoft technologies • Design distributed systems, microservices, APIs, and event-driven architectures • Partner with Product and Engineering teams to deliver high-impact features and improve system design • Architect and evolve enterprise-scale data warehouse, data lake, and lakehouse environments • Establish data modeling standards, data quality controls, governance practices, and reconciliation processes • Own Azure infrastructure strategy across development, staging, and production environments • Design, build, and maintain CI/CD pipelines, deployment automation, and release engineering practices • Collaborate closely with Data Science to operationalize analytics, AI, and machine learning solutions

Role Description Our client is seeking a AI Backend Engineer to build and operate the backend infrastructure that powers AI-driven experiences across its products. The role focuses on owning the inference and orchestration layer that sits between AI models and end users, ensuring every interaction is fast, reliable, scalable, and cost-efficient. Working closely with engineering and AI teams, this position will play a key role in designing production-grade backend services, optimizing system performance, and delivering robust AI-powered features across mobile and desktop platforms. Key Responsibilities - Build, maintain, and operate backend systems that power AI-enabled features in production. - Design and implement AI inference pipelines, orchestration layers, and service architectures around AI models. - Develop scalable, high-performance APIs that integrate seamlessly with frontend applications and machine learning systems. - Optimize system performance by improving inference latency, throughput, caching, batching, and streaming capabilities. - Own production operations, including monitoring, logging, alerting, and incident response. - Troubleshoot and resolve issues within distributed systems to ensure service reliability and stability. - Continuously improve backend architecture and production systems based on operational insights and real-world usage. - Collaborate with cross-functional teams to deliver reliable, scalable, and high-quality AI-powered solutions. Qualifications - Strong backend engineering experience in production environments. - Proven experience building and operating high-throughput, low-latency backend services. - Experience designing scalable APIs and distributed systems. - Familiarity with AI inference patterns, including Large Language Models (LLMs), embeddings, and multimodal AI systems. - Strong debugging and troubleshooting skills within distributed production environments. - Demonstrated ability to deliver production-ready solutions while iterating based on real-world system performance. - Excellent analytical, problem-solving, and collaboration skills. Technical Skills - Experience with Python. - Experience with Node.js. - Experience with PyTorch. - Experience with OpenAI, Anthropic, or open-source Large Language Models (LLMs). - Experience with SQL and NoSQL databases. - Experience with Kubernetes. - Experience with Docker.