• Write clean, readable code; • Execute both trivial and non-trivial initiatives; • Take ownership of the received initiative; • Coordinate cross-team interactions within the framework of task work.

Role Description We are building a next-generation AI-driven platform that enables developers, creators, and enterprises to design scalable, secure, and human-centered AI experiences. As adoption grows, we are looking for a Backend Ops Engineer to take full ownership of infrastructure, ensuring high reliability, performance, and cost efficiency. This role is critical in centralizing DevOps and infrastructure responsibilities—enabling faster deployments, reducing operational risks, optimizing cloud costs, and building a strong foundation for scalability and compliance. You will also play a key role in integrating AI into infrastructure operations, shaping the future of intelligent DevOps systems. Key Responsibilities - Initial Focus (First Quarter) - Implement AI-powered operations such as log analysis, automated infrastructure updates, and predictive scaling alerts - Benchmark cloud and edge services and prototype scalability improvements - Build self-healing infrastructure pipelines that demonstrate advanced AI capabilities - Ongoing Responsibilities - Design, automate, and manage cloud infrastructure using Terraform and AWS services (ECS/Fargate, RDS, S3, IAM) - Build and maintain CI/CD pipelines using GitHub Actions for efficient and reliable deployments - Implement observability and monitoring systems using tools like Prometheus, Grafana, OpenTelemetry, and Sentry - Manage containerization using Docker and troubleshoot performance issues under load - Collaborate with backend teams to ensure low-latency, cost-effective, and scalable systems - Continuously improve system reliability, uptime, and incident response processes Growth Path - Progress into a Staff Platform Engineer or Lead SRE role - Own end-to-end platform infrastructure - Contribute to building enterprise-ready deployment frameworks - Help define best practices for AI-driven DevOps systems Qualifications - 2–3+ years of experience in DevOps or Site Reliability Engineering roles - Strong expertise in AWS (ECS/Fargate, RDS, S3, CloudWatch, IAM) - Hands-on experience with Terraform and infrastructure-as-code practices - Proven experience with CI/CD pipelines (GitHub Actions preferred) - Strong knowledge of Docker and containerized environments - Experience with observability tools such as Prometheus, Grafana, OpenTelemetry, or Sentry - Demonstrated ability to debug and resolve infrastructure issues under load AI & Technical Mindset - Interest or experience in integrating AI into DevOps workflows - Exposure to LLM APIs or AI-driven automation tools is a plus Nice to Have - Familiarity with compliance frameworks such as SOC 2 or GDPR - Experience with multi-cloud environments (AWS, GCP, Azure) - Proficiency in Python for scripting and automation - Knowledge of infrastructure security best practices - Experience with cloud platforms like DigitalOcean or cloud migration projects Soft Skills - Strong ownership mindset with a proactive approach - Clear communication skills to explain technical trade-offs - Bias toward automation and continuous improvement - Ability to work effectively in fast-paced, evolving environments Key Skills - AWS ECS / Fargate - Terraform - CI/CD Pipelines - Docker - Observability & Monitoring

• Own the architecture, design, and evolution of our Kubernetes-based platform on AWS, ensuring scalability, resilience, and operational excellence • Develop, maintain, and optimize Kubernetes infrastructure using Infrastructure as Code (CDK), enforcing best practices and architectural standards • Act as the technical guide and domain expert for Kubernetes architecture, collaborating closely with the Architecture team to bridge high-level strategy with implementation and guide engineering teams with clear patterns, reference architectures, and best-practice recommendations • Lead technical decision-making across multiple teams, providing mentorship, design reviews, and hands-on support to drive platform consistency and quality • Drive proactive improvements across the platform, identifying scaling issues, reliability gaps, or operational inefficiencies before they become problems • Design and implement secure, compliant, and highly observable Kubernetes environments, integrating monitoring, logging, and alerting systems • Lead and support the migration of non-cloud-native applications to the new infrastructure, assessing readiness and implementing best practices for scalability and maintainability • Champion automation and GitOps practices to reduce manual work, eliminate drift, and improve release velocity • Lead cross-team initiatives and influence technical direction outside your immediate organization, driving adoption of cloud-native best practices • Participate in on-call rotations and contribute to incident response and root cause analysis

• Develop and maintain Java microservices using Spring Boot. • Assist in designing and implementing scalable and reliable features. • Troubleshoot and provide support for existing services under guidance from senior engineers. • Collaborate with product managers, QA, and peers to deliver high-quality software. • Learn and apply best practices for cloud-based application development.