You will be joining our team as a System Development Engineer focusing on the Hybrid Scientific Computing Stack. A strong background in computer science and software development is required for this role, and knowledge of quantum computing would be an added advantage. Your responsibilities will include working on backend services such as FastAPI, Celery, OAuth, PostgreSQL, and Redis. You will also be involved in hybrid job orchestration using tools like Celery, RabbitMQ, Slurm, and Kubernetes. Containerized workflows using Docker, Singularity, and Helm will be part of your tasks. Monitoring and observability tasks will involve tools like Prometheus, Grafana, Loki, and Flower. Cloud-based deployment on platforms like GCP, AWS, and Azure, as well as secure on-prem server management, will also be within your purview. Additionally, you will work on scientific environments involving CUDA, Qiskit, Conda, GROMACS, and Lmod. To qualify for this position, you should hold a minimum Bachelor's Degree in Computer Science or related fields and have at least 2 years of professional work experience in full-stack systems engineering. Proficiency in Python (FastAPI/Celery), Linux (Ubuntu/Debian), and DevOps is required. Familiarity with cloud-native tools like Docker, Kubernetes, Helm, and GitHub Actions is essential. Experience with Slurm, GPU resource allocation, and secure job execution will be beneficial. Any familiarity with quantum SDKs such as Qiskit, PennyLane, and Cirq will be considered a bonus.,
You will be joining our team as a Systems Development Engineer for the Hybrid Scientific Computing Stack. A strong background in computer science and software development is essential for this role, with knowledge of quantum computing considered a valuable asset. Your responsibilities will include managing backend services such as FastAPI, Celery, OAuth, PostgreSQL, and Redis. You will also be involved in hybrid job orchestration using tools like Celery, RabbitMQ, Slurm, and Kubernetes, as well as working on containerized workflows with Docker, Singularity, Helm, and Kubernetes. Monitoring and observability tasks will involve tools like Prometheus, Grafana, Loki, and Flower. Additionally, you will be responsible for cloud-based deployment on platforms like GCP, AWS, and Azure, as well as secure on-prem server management including GPU/CPU scheduling, RBAC, and SSH-only access. Familiarity with scientific environments such as CUDA, Qiskit, Conda, GROMACS, and Lmod will also be part of your role. To qualify for this position, you should hold a minimum Bachelor's Degree in Computer Science or related fields and have at least 2 years of professional work experience in full-stack systems engineering. Proficiency in Python (FastAPI/Celery), Linux (Ubuntu/Debian), and DevOps is required. You should also be familiar with cloud-native tools like Docker, Kubernetes, Helm, and GitHub Actions. Experience with Slurm, GPU resource allocation, and secure job execution will be beneficial. Any familiarity with quantum SDKs such as Qiskit, PennyLane, and Cirq will be considered a bonus.,
Position Overview We are looking for a motivated Backend Systems Engineer to join our team. Candidates should have a strong background in computer science and software development. Knowledge of quantum computing is a plus. Key Responsibilities • Design and develop robust, scalable, and secure backend services using Python (FastAPI/Django/Flask) and async frameworks. • Implement RESTful APIs following best practices in OpenAPI/Swagger, versioning, validation (Pydantic), and error handling. • Architect and manage job orchestration systems using Celery, RabbitMQ/Redis, and integrate with various compute backends. • Build and maintain authentication & authorization mechanisms, leveraging JWT, OAuth2.0, Auth0, and enforcing secure coding practices (CORS, HTTPS, CSRF, RBAC). • Optimize and manage storage systems across relational (PostgreSQL), NoSQL (MongoDB), caching (Redis), and object storage (S3/MinIO) layers. • Implement monitoring, logging, and observability pipelines using Prometheus, Grafana, Loki/ELK, and Flower for task tracking. • Write comprehensive tests and enforce code quality via pytest, pre-commit hooks, and integration testing tools. • Maintain internal documentation (Swagger, MkDocs) and collaborate with the team via GitHub, Slack, Notion, and task trackers. • Configure Slurm Workload Manager, define partitions, QOS policies, and ensure fair share scheduling with compute/resource limits (CPU, memory, GPU). • Provision users, groups, and storage layout with per-team isolation, Linux ACLs, shared scratch, and persistent directories. • Manage environment module systems (Lmod) and multi-version support (CUDA, GROMACS, Qiskit, Conda environments). • Implement robust monitoring, alerting, and audit pipelines using Prometheus, Grafana, node_exporter, dcgm-exporter, Slurm exporters, and container monitors (cAdvisor). • Enforce access control and secure job execution via rbash, SSH key-only login, restricted shells, and centralized logging (journald/auditd). • Automate nightly backups and disaster recovery with NAS + Rsync, system image snapshots, and maintain documented recovery playbooks. • Author and maintain server provisioning scripts, onboarding SOPs, and a centralized repository of job templates, modulefiles, and update logs. Qualifications Required: • 3+ years of experience in full-stack/systems development and deployment. • Strong hands-on experience with FastAPI and RESTful API design. • Deep understanding of asynchronous programming, ORMs (SQLAlchemy/Tortoise), and ASGI/WSGI servers. • Proven experience with Celery and task queues for async job orchestration. • Solid understanding of authentication/security best practices and Auth0 or similar platforms. • Experience with PostgreSQL, Redis, and object storage solutions like AWS S3. • Proficiency with Docker environments. • Familiarity with automated testing (pytest, Postman), and observability tools (Grafana, Prometheus). • Strong experience with Linux system administration (Ubuntu/Debian preferred) in high-performance compute (HPC) or research lab settings. • Hands-on experience setting up and managing Slurm, cgroups, Gres/GPU configs, and job execution templates. • Comfortable configuring and debugging GPU drivers, CUDA toolkits, and tools like nvidia-container-toolkit, nvidia-smi, and MPS. • Experience setting up and maintaining Prometheus, Grafana, and exporters for system, GPU, and Slurm metrics. • Proficient with shell scripting (bash) and basic configuration automation tools (e.g., Ansible or cloud-init). • Understanding of container runtimes (Docker, Singularity) in HPC-like workflows. Preferred: • Exposure to quantum computing SDKs (Qiskit, Braket, Cirq, PennyLane) or SLURM/HPC job schedulers. • Experience deploying to on-prem/HPC environments over SSH or VPN. • Knowledge of load testing tools (Locust, k6) and log aggregation pipelines (Loki, ELK). • Background in real-time monitoring dashboards, admin tools, or user activity audit trails. • Experience architecting on-prem/hybrid deployments integrating quantum SDKs (Qiskit, PennyLane, Cirq) with classical AI/ML workloads. • Experience configuring NAS, backup automation (cron + rsync), and snapshot-based recovery (Clonezilla, Timeshift). • Knowledge of environment management systems like Lmod, Spack, or Conda in HPC/scientific computing environments. • Experience enforcing security hardening policies: SSH key-only auth, restricted shells, user quotas, and RBAC patterns in Linux. What We Offer • Opportunity to work with cutting-edge quantum technologies. • Innovative and collaborative startup environment. • Competitive salary and benefits. • Professional development and collaboration opportunities.
You will be joining the team as a System Development Engineer focusing on the Hybrid Scientific Computing Stack. A strong background in computer science and software development is required for this role, and knowledge of quantum computing would be an added advantage. - Work on backend services such as FastAPI, Celery, OAuth, PostgreSQL, and Redis - Be involved in hybrid job orchestration using tools like Celery, RabbitMQ, Slurm, and Kubernetes - Manage containerized workflows using Docker, Singularity, and Helm - Handle monitoring and observability tasks with tools like Prometheus, Grafana, Loki, and Flower - Deploy cloud-based solutions on platforms like GCP, AWS, and Azure, as well as manage secure on-prem servers - Work on scientific environments involving CUDA, Qiskit, Conda, GROMACS, and Lmod Qualifications Required: - Hold a minimum Bachelor's Degree in Computer Science or related fields - Have at least 2 years of professional work experience in full-stack systems engineering - Proficiency in Python (FastAPI/Celery), Linux (Ubuntu/Debian), and DevOps - Familiarity with cloud-native tools like Docker, Kubernetes, Helm, and GitHub Actions - Experience with Slurm, GPU resource allocation, and secure job execution will be beneficial - Any familiarity with quantum SDKs such as Qiskit, PennyLane, and Cirq will be considered a bonus.,
As a Systems Development Engineer for the Hybrid Scientific Computing Stack, your role will involve managing backend services such as FastAPI, Celery, OAuth, PostgreSQL, and Redis. Additionally, you will be responsible for orchestrating hybrid jobs using tools like Celery, RabbitMQ, Slurm, and Kubernetes. You will also work on containerized workflows with Docker, Singularity, Helm, and Kubernetes. Monitoring and observability tasks will require the use of tools like Prometheus, Grafana, Loki, and Flower. Cloud-based deployment on platforms like GCP, AWS, and Azure, as well as secure on-prem server management including GPU/CPU scheduling, RBAC, and SSH-only access, will also be under your responsibilities. Familiarity with scientific environments such as CUDA, Qiskit, Conda, GROMACS, and Lmod is expected in this role. Key Responsibilities: - Manage backend services such as FastAPI, Celery, OAuth, PostgreSQL, and Redis - Orchestrate hybrid jobs using Celery, RabbitMQ, Slurm, and Kubernetes - Work on containerized workflows with Docker, Singularity, Helm, and Kubernetes - Monitor systems using tools like Prometheus, Grafana, Loki, and Flower - Deploy on cloud platforms like GCP, AWS, and Azure - Manage on-prem servers with GPU/CPU scheduling, RBAC, and SSH-only access - Utilize scientific environments including CUDA, Qiskit, Conda, GROMACS, and Lmod Qualifications Required: - Minimum Bachelor's Degree in Computer Science or related fields - At least 2 years of professional work experience in full-stack systems engineering - Proficiency in Python (FastAPI/Celery), Linux (Ubuntu/Debian), and DevOps - Familiarity with cloud-native tools like Docker, Kubernetes, Helm, and GitHub Actions - Experience with Slurm, GPU resource allocation, and secure job execution - Familiarity with quantum SDKs such as Qiskit, PennyLane, and Cirq would be a bonus,