Mlabs
Senior Infrastructure Engineer
United States · Senior · Full-time
No sponsorship$220k-$300kDetected 14 days ago
PythonRustNode.jsDistributed SystemsCode ReviewSQLNoSQLAWSGCPCloud PlatformsDockerKubernetesTerraformCI/CDJenkinsPrometheusGrafanaDatadogDevOpsSite Reliability EngineeringCybersecurityProduct ManagementProduct StrategyLeadership
About the role
- Automation & CI/CD: Automate infrastructure provisioning and application deployments utilizing Terraform, Jenkins, and advanced CI/CD pipelines.
Responsibilities
- Infrastructure Design & Scalability: Design, build, and maintain cloud infrastructure with a steadfast focus on scalability, high availability, and security.
- Containerization & Orchestration: Architect, manage, and scale containerized and orchestrated environments leveraging Docker and Kubernetes.
- Observability & Monitoring: Implement and manage robust observability and monitoring frameworks across logs, metrics, and traces using Datadog.
- Performance Optimization: Optimize the reliability and performance of Node.js applications and underlying backend services.
- Security Hardening: Configure and manage secure enclaves (such as AWS Nitro Enclaves) to isolate and harden critical cryptographic and transactional workflows.
- Cross-Functional Collaboration: Partner with product and security leadership to align infrastructure decisions with the long-term product roadmap and risk-mitigation strategies.
- Design, build, and maintain cloud infrastructure with a steadfast focus on scalability, high availability, and security.
- Architect, manage, and scale containerized and orchestrated environments leveraging Docker and Kubernetes.
- Configure and manage secure enclaves (such as AWS Nitro Enclaves) to isolate and harden critical cryptographic and transactional workflows.
- Partner with product and security leadership to align infrastructure decisions with the long-term product roadmap and risk-mitigation strategies.
Requirements
- Document system architectures thoroughly, promote internal knowledge sharing, and technically support client-facing discussions when required.
- Strong, production-level expertise with AWS.
- Experience with GCP, IBM Cloud, or Thales HSMs is highly advantageous.
- Advanced proficiency with Terraform and automated CI/CD pipeline management.
- Deep operational knowledge of Docker, Kubernetes, and containerized microservices.
- Proficiency in scripting and systems programming languages, specifically Python, Rust, or TypeScript.
- Outstanding communication skills and the demonstrated ability to operate effectively and make sound technical decisions under pressure.
- Critical Thinking, Verbal Reasoning (English proficiency testing), Attention to Detail (Textual), Numerical Reasoning, and Problem Solving.
- Documentation & Support: Document system architectures thoroughly, promote internal knowledge sharing, and technically support client-facing discussions when required.
- Infrastructure-as-Code: Advanced proficiency with Terraform and automated CI/CD pipeline management.
Nice to have
- Prior experience working directly with blockchain networks, node infrastructure, and smart contracts is highly desirable.
- Opportunity to work at the forefront of financial technology and decentralized systems.
- Collaborative environment alongside industry-leading cryptographers and engineers.
- Candidates will receive an invitation containing five distinct components: Critical Thinking, Verbal Reasoning (English proficiency testing), Attention to Detail (Textual), Numerical Reasoning, and Problem Solving.
- Each section includes untimed practice questions to allow candidates to familiarize themselves with the format.
- Once the official section begins, there is a strict 10-minute time limit per part.
- Due to the fast-paced nature of this test, candidates are highly encouraged to complete the assessment in a quiet, distraction-free environment where intense focus is possible.
- Take-Home Technical Challenge: A practical coding assessment focusing on real-world engineering problems, which can be completed in the programming language of the candidate's choice.
Skills
- Proven experience in administering, tuning, and scaling both SQL and NoSQL databases.
- Familiarity with modern observability platforms (e.g., Datadog, ELK stack, or Prometheus/Grafana).
- Cloud Architecture: Strong, production-level expertise with AWS.
Compensation
- $220k-$300k
Benefits
- An introductory conversation with the Co-CEO to discuss the candidate's background, career goals, and high-level alignment with the company vision.
- Hiring Manager Interview (30 Minutes): An introductory conversation with the Co-CEO to discuss the candidate's background, career goals, and high-level alignment with the company vision.
Company info
- A closing conversation with the CTO to align on final expectations, technical strategy, and future growth.
- Due to the high volume of applications we anticipate, we regret that we are unable to provide individual feedback to all candidates.
- At MLabs, we are committed to offer equal opportunities to all candidates.
- We ensure no discrimination, accessible job adverts, and providing information in accessible formats.
- Our goal is to foster a diverse, inclusive workplace with equal opportunities for all.
- If you need any reasonable adjustments during any part of the hiring process or you would like to see the job-advert in an accessible format please let us know at the earliest opportunity by emailing human-resources@mlabs.city.
- MLabs Ltd collects and processes the personal information you provide such as your contact details, work history, resume, and other relevant data for recruitment purposes only.
- Your data may be shared only with clients and trusted partners where necessary for recruitment purposes.
- You may request the deletion of your data or withdraw your consent at any time by contacting legal@mlabs.city.
- Commitment to Equality and Accessibility: At MLabs, we are committed to offer equal opportunities to all candidates.
This listing is sourced directly from Mlabs's careers page and normalized into a canonical job model.