Cloud Engineer
First seen by Alion on Nov 10, 2026.
Location: US Based (Full-Time, Remote) or International Contractor (Full-Time, Remote)
If US-Based:
This will be a remote position based in the United States. Knack offers a complete benefits package to those working in the United States. Employees must be available during standard US business hours and maintain their primary work location within the US. Any extended time working outside the United States requires prior written approval.
International Contractor:
This is a full-time, remote position, but candidates must have four hours overlap with Eastern timezone.
Role Overview
Knack runs thousands of customer applications across multiple global regions, including dedicated private environments. As a Cloud Engineer, you’ll own and evolve that infrastructure, harden it to meet SOC 2, HIPAA, and customer security requirements, and build the infrastructure behind our growing AI capabilities.
We’re an AI-forward team. You don’t need to type every Terraform block, but you do need to understand what’s happening, direct AI tools well, verify their work, and own the outcome. This role includes a weekly 24/7 on-call rotation.
About Knack
Knack is an AI-powered no-code software development platform enabling organizations to manage, analyze, and share business data. The no-code market is growing at over 30% annually and projected to be almost $200B by 2030. Founded in 2010, Knack has grown into a leading player in the no-code movement, enabling businesses, teams, and individuals to build custom applications without writing a single line of code.
Serving a wide range of industries, from healthcare and education to finance and nonprofits, and organizations from small businesses to Fortune 500s, Knack enables users to boost data visibility and streamline operations.
To date, the platform has powered 400,000 apps and stored more than 5 billion data records for over 15,000 customers. Its enterprise-grade functionality includes an AI-powered visual builder, robust data structures, user access controls, and automation capabilities, all delivered by a fully remote team committed to trust, continuous improvement, and measurable impact.
Key Responsibilities
Run AWS infrastructure as code, with AI in the loop
- Manage AWS infrastructure through Terraform using our pull-request-based GitOps workflow, and resolve configuration drift across regions.
- Use AI tools to draft, review, and explain Terraform changes, then verify every plan before it merges. You own every change you approve, regardless of who or what wrote it.
- Maintain reusable modules and the standards that make AI-generated changes safe and consistent.
Make AWS and Claude work together
- Help design and operate how AI assistants work with our AWS environments, for investigation, analysis, incident triage, and infrastructure changes.
- Define the IAM roles, permission boundaries, logging, and approval gates that govern what AI tools can see and do.
- Evaluate AI access for blast radius and auditability.
Implement security controls with our security lead
- Enforce encryption at rest and TLS in transit, tighten IAM and S3 permissions, manage WAF rules and security headers, and rotate secrets.
- Drive pentest and audit findings to verified fixes in every environment.
- Secure the AI tooling itself, including agent credentials, secrets handling, MCP server exposure, and prompt injection risk.
Support compliance and audits
- Configure and maintain SOC 2 and HIPAA controls such as log retention, alarms, VPC flow logs, and backups.
- Ensure AI-assisted changes keep the same review, approval, and audit trail as any other change.
- Gather audit evidence and help maintain security tooling.
Build monitoring, alerting, and runbooks
- Create dashboards and monitors that catch issues before customers do, and tune noisy alerts.
- Keep runbooks current and written so that both people and AI assistants can follow them.
Keep systems patched and current
Lead OS upgrades, runtime and end-of-life migrations, dependency updates, and certificate renewals.
Operate and scale databases and customer environments
- Tune, resize, and secure databases on multiple platforms.
- Provision or decommission dedicated customer servers for Sales and Support.
Resolve escalations and automate repeat work
- Troubleshoot production issues for Support, Sales, and Engineering.
- Replace recurring manual tasks with automation, CI/CD improvements, or self-service tooling, using AI to move faster while verifying what it produces.
Participate in on-call
Participate in our weekly 24/7 on-call rotation, responding to production alerts and following up with fixes or runbook updates so the same issue does not repeat.
Qualifications
Experience
- 3-5 years in cloud infrastructure, DevOps, SRE, or platform engineering, including 2+ years working in AWS production environments. Looking for someone who has experience shipping infrastructure changes through code review. Depth matters more than the number.
- Experience operating a multi-tenant SaaS platform at scale, including participating in a 24/7 on-call rotation.
- A degree is not required. Demonstrated hands-on experience counts equally.
Technical depth
- Deep AWS knowledge across compute, networking, and security services, such as EC2, ECS/Fargate, Lambda, VPC, IAM, S3, CloudFront, and RDS.
- Strong Terraform understanding, including module design, state management, and pull-request-based CI/CD workflows. You can read a plan and explain what will be created, changed, or destroyed, and where the risk is.
- Working knowledge of cloud security fundamentals: least-privilege IAM, encryption in transit and at rest, network security groups and WAFs, secrets management, and vulnerability remediation.
- Hands-on experience with monitoring and logging tools and building actionable alerts.
- Experience administering relational and NoSQL databases in production.
- Solid Linux and container (Docker) fundamentals.
- Able to read and reason about code and scripts in Python, Go, Bash, or Node.js/TypeScript, including large JavaScript/TypeScript codebases when tracing infrastructure-related bugs. You do not need to write them from scratch.
How you work with AI
Daily, practical use of AI tools like Claude, with the judgment to critically review AI-generated scripts, Terraform, and IAM policies, and accountability for everything you ship.
Preferred Qualifications
- Experience supporting compliance frameworks such as SOC 2, HIPAA, FedRAMP, or ISO 27001, including evidence collection and control implementation.
- Experience with AWS GovCloud or other regulated or isolated environments.
- A security certification or equivalent depth, such as AWS Certified Security - Specialty, CompTIA Security+, or CCSP, or experience with SIEM, intrusion detection, or threat modeling.
- Experience running AI/LLM infrastructure, such as Amazon Bedrock, LLM gateways, vector databases, or MCP servers.
- Experience governing AI agent access to cloud environments, including scoped IAM roles, session logging, and approval workflows.
- Familiarity with GitOps tooling for Terraform and CI/CD platforms such as CircleCI, GitHub Actions, or AWS CodeBuild.
- Experience with data warehouses and pipelines (for example, Redshift and ETL tooling).
- Kubernetes/EKS experience.
- Experience at a small or early-stage company where you wore many hats.
Interviews will be recorded and transcribed by an AI notetaking tool so our team can focus on the conversation and review it accurately later. Notes are used only for evaluating your application. You can opt out at any time by letting your recruiter know.