Senior Cloud Engineer

Posted:
12/3/2024, 6:49:22 AM

Experience Level(s):
Senior

Field(s):
DevOps & Infrastructure ⋅ Software Engineering

Workplace Type:
Hybrid

Lirio is a technology/software company that provides expertise in a variety of behavioral science domains (e.g., behavioral economics, social psychology, public health), data science, and machine learning to drive consumer engagement, close gaps in preventive and chronic care, and promote health and well-being across an individual’s lifespan. Lirio’s behavior change AI platform unites behavioral science with advanced artificial intelligence (AI) to deliver Precision Nudging health interventions. Precision Nudging is the application of behavioral science to health interventions personalized by AI to each individual that overcome barriers to action at the right time and place for scalable behavior change. 

 

Position Summary 

Lirio is offering an exciting opportunity for an experienced cloud engineer skilled in infrastructure, supporting and contributing to software engineering, technical leadership, solutions architecture, distributed systems, and cloud-native and cloud-agnostic technologies to join us in meeting the challenge to improve health for everyone and develop, maintain, and improve both our SaaS product cloud infrastructure and the infrastructure components of our client deployable enterprise capability for our Kubernetes-based behavior change AI platform. This is a chance to contribute to Lirio’s core platform, SaaS product, and enterprise solution, and work with innovative infrastructure, multiple cloud providers, and cloud-agnostic technologies and change lives by improving health. 

The Senior Cloud Engineer is responsible for helping define and support cloud infrastructure architecture, cloud engineering practices, infrastructure automation, and related tooling for Lirio applications, products, services, and engineers. This role provides end to end support to technical engineers for computing platforms and resources and offers guidance in both tooling and team integrations to mitigate risks and enhance innovation. This candidate will provide technical support by aiding cloud, software, data, and machine learning engineers in designing and architecting cloud-agnostic and Cloud Native Computing Foundation (CNCF) aligned cloud-native solutions, acquiring infrastructure, and deploying them at scale; providing technical support to cloud practices and architectural approaches; supporting and running Lirio’s Software-As-A-Service (SAAS) solutions while helping Lirio and our clients with strategic integration of custom packaged solutions like an enterprise solution to be deployed within client cloud environments as needed. 

To succeed in this role, the Senior Cloud Engineer will need experience with infrastructure-as-code tools, Kubernetes, and cloud platform providers like Microsoft Azure and Amazon Web Services.  A level of professional software development experience in Java, Python, or Go is highly preferred. Along with the engineering duties, this position also has a support component, so experience and a willingness to support customers deploying software to public and private clouds is highly preferred as well.  

This role is remote within the US, with the opportunity to be hybrid if located in TN. Applicants must reside in the US full-time. 

Essential Duties & Responsibilities 

  • Support the design and planning of cloud-agnostic solutions capable of being deployed to multiple cloud providers and customer public cloud and private data centers 
  • Design, implement, test, deploy, maintain, and support cloud-native and cloud-agnostic self-healing infrastructure across environments, multiple cloud providers, and customer data centers as a top-level contributor 
  • Plan, implement, and support a developer platform to improve self-service 
  • Collaborate with development teams to evaluate and identify optimal cloud services and infrastructure solutions and address issues as they arise 
  • Review existing systems and offer recommendations for improvement 
  • Identify, analyze, mitigate and resolve infrastructure issues, vulnerabilities, and application deployment issues through monitoring, scanning, observability, and processes  
  • Support and improve Lirio’s engineering practices including an emphasis on quality and security 
  • Document decisions, work product, and cloud practices 
  • Review code, designs, and contributions from others, promoting stability, security, compliance, scalability, readability, and maintainability 
  • Write clean and maintainable code/infrastructure-as-code (IaC) 
  • Assist in project planning, estimation, and resource allocation 
  • Help manage infrastructure spend efficiency 
  • Implement and support build & CI/CD pipeline engineering efforts as needed 
  • Pursue continuous learning through individual study, online courses, product documentation, and community resources to bring innovation to the technical organization 

Basic Qualifications 

  • 5+ years developing public and private cloud infrastructure. 
  • 2+ years development and deployment of Java or Python tech stacks. 
  • Adept at utilizing DevSecOps principles to collaborate with other product engineering roles 
  • Knowledge and hands-on experience with cloud service providers Azure and AWS. Oracle OCI experience a plus. 
  • Experience deploying and supporting the same software on multiple clouds at the same time. 
  • Experience with core cloud services including compute, storage, networking, security, and databases 
  • Experience with containerization technologies like Docker and Kubernetes.  
  • Experience with event-driven architecture. 
  • Experience with Kubernetes deployment tools. Helm and ArgoCD preferred. 
  • Experience deploying and supporting distributed systems on public and private cloud infrastructure 
  • Experience with Datadog or other observability platforms  
  • Experience with infrastructure-as-code and tools. Helm, Terraform, and Ansible preferred. 
  • Experience securing networks and other infrastructure end-to-end, in-transit and at-rest 
  • Proficiency in scripting languages (e.g., Python, Bash) for automation tasks 
  • Working knowledge of Linux 
  • Demonstratable command of a programming language where Java, Python, and Go are preferred though demonstrable, articulable skills with TypeScript, C#, or other languages will be considered 
  • Comfortable in a fast-paced environment 
  • Ability to quickly learn company terminology and processes 
  • Collaborative / team oriented and flexible 
  • Self-starter with strong time management and work planning skills 
  • Desire to innovate, grow, and make a difference in the world by working with modern technology and a great team to achieve worthwhile goals and improve health for everyone 
  • Bachelor’s Degree in a technical field or equivalent work experience 

Preferred Qualifications 

  • Experience with microservices and eventually consistent architectures 
  • Experience with event-driven architectures, asynchronous messaging, and Apache Kafka 
  • Experience working with production data and event infrastructures in Kubernetes 
  • Software engineering background or previously held a software engineering role 
  • SRE experience with large scale cloud-based systems 
  • Experience building infrastructure for Data and Machine Learning teams 
  • Experience with build tools like Gradle, Poetry, Azure DevOps Pipelines, and Github Actions 
  • Experience working with Protected Health Information (PHI)

Benefits

  • Medical (HSA available) 
  • Dental 
  • Vision 
  • Short-term & long-term disability (company-paid) 
  • Life & AD&D (company-paid) 
  • 401K with company match 
  • 10 paid holidays + holiday week company closure 
  • Flexible time off policy 
  • Work from home 
  • Job Salary Range: $140,000-$165,000

 

Lirio

Website: https://lirio.com/

Headquarter Location: Knoxville, Tennessee, United States

Employee Count: 51-100

Year Founded: 2016

IPO Status: Private

Last Funding Type: Debt Financing

Industries: Artificial Intelligence (AI) ⋅ Health Care ⋅ Information Technology ⋅ Machine Learning