Remote Ai Infrastructure Engineer Jobs in Tulsa, OK

Senior QA Engineer

At Volt Labs, we're building the infrastructure layer behind modern business messaging. Our platform helps companies navigate messaging compliance, onboarding, deliverability, routing, and operational complexity across carriers and providers.

We are a remote-first, high-ownership team operating in a fast-moving growth environment. We care deeply about builder mentality, operational excellence, speed with accountability, and creating systems that scale.

We are looking for engineers who want to help define the future of Messaging Ops while using AI as a core part of how they build, test, troubleshoot, and improve software quality.

We are hiring a Senior QA Engineer to own and scale quality processes across Volt's platform, infrastructure, and customer-facing systems.

This role carries ownership: defining test strategy, building automation infrastructure, driving release confidence, and setting the quality bar for the engineering team. You will work closely with Engineering, Product, Customer Operations, and Leadership to improve quality standards and reduce production risk as the platform scales rapidly.

This is not a traditional manual-only QA role. We're looking for someone who thinks like a systems builder and who can define strategy, build automation infrastructure, and operate with enough technical depth to own QA environment management within our AWS infrastructure, without needing to wait on a dedicated DevOps resource.

Just as important: this is a team role. Our engineering group is small, tight-knit, and collaborative. We cover for each other, give candid feedback without ego, and take pride in raising the collective quality of the work. We're looking for someone who adds to that culture, someone who wants to build great things alongside great people.

The ideal candidate is highly organized, technically deep, process-oriented, and comfortable operating with senior-level ownership in a startup environment where systems are evolving quickly.

• Own and continuously improve QA strategy, processes, and standards across engineering and product workflows
• Design and build automated testing infrastructure for platform reliability and release confidence Not just execute tests, but build the systems that run them
• Define and maintain test plans, regression testing, and release validation processes
• Identify gaps in testing coverage and operational risk areas, and drive resolution
• Partner with Engineering and Product to set and enforce quality gates in the development and release workflow
• Own staging and QA environment management within AWS, including deployment of code into pre-production environments
• Document bugs clearly with reproducible steps and business impact context
• Drive observability, monitoring validation, and production issue analysis
• Lead API testing, workflow testing, and operational scenario validation with an emphasis on back-end platform and infrastructure coverage over UI testing
• Actively support peers through knowledge sharing, filling coverage gaps, and contributing to team-wide quality standards, not just owning your own test surface
• Leverage AI tooling to improve test generation, bug analysis, automation, documentation, and troubleshooting
• Build and maintain scalable QA documentation, standards, and operational playbooks

AI is not an add-on at Volt, it's woven into how we build and test. We're excited about what's possible when strong QA fundamentals meet modern AI-enabled workflows, and we're looking for someone who shares that excitement. Ideally, you've moved beyond dabbling, you've been part of a team that has transitioned to AI-augmented QA practices, and you can bring that experience with you: what worked, what didn't, and how to make it stick. Because this is platform and infrastructure work, high-scale, transactional, API-driven systems, that kind of applied experience matters far more to us than a background in UI or front-end testing.

What that looks like in practice:

• Systematic use of AI-assisted test generation and coverage analysis, not just ad hoc tooling
• AI-assisted bug analysis and triage
• Automated regression coverage at scale
• Release validation automation
• Test documentation generation
• Operational workflow simulations
• Root-cause analysis support
• Helping the broader team grow its own AI-enabled QA practices over time we're all learning together

• Proven experience in senior QA engineering, software testing, or release management
• Strong understanding of QA methodologies, testing lifecycles, and test strategy at the system level
• Experience building and owning automated testing frameworks and infrastructure, not just using them
• Strong API testing and back-end platform testing experience
• Ability to think strategically about operational risk, edge cases, and quality at scale
• Comfort with AWS environments and the ability to manage deployments into staging and QA environments independently
• Strong documentation and communication skills
• Experience working cross-functionally with Engineering and Product teams, with the credibility to influence quality standards
• Ability to operate independently and drive quality initiatives while actively supporting and collaborating with a small, high-trust team
• A collaborative, low-ego approach to peer feedback and shared ownership of quality
• Comfortable operating in fast-moving startup environments with high ownership expectations
• Strong troubleshooting and analytical mindset
• Actual, hands-on experience with AI-enabled testing workflows and agentic tooling, ideally in an environment that has made the shift from traditional QA practices

• Experience testing high-volume platforms or messaging systems
• Hands-on experience with AWS services relevant to deployment and environment management (ECS, CodePipeline, CloudWatch, or similar)
• Familiarity with CI/CD pipelines and deployment workflows
• Experience with observability and monitoring platforms
• Experience with performance or load testing at scale
• Familiarity with SQL and database validation workflows
• Experience building QA automation infrastructure from the ground up
• Deep familiarity with agentic tooling and AI-assisted QA at the team or org level

• Remote-first team with high ownership and accountability
• Small, highly collaborative environment. Everyone fills in, no one operates on an island
• Fast iteration cycles and direct access to leadership
• Strong builder culture with low ego and a commitment to peer feedback
• Bias toward action, clarity, and operational excellence
• AI-forward engineering mindset, actively evolving our practices

• Opportunity to build and own foundational QA systems during a major growth stage
• High-impact role with visibility across the business and direct influence on engineering quality
• Ability to define quality standards and shape engineering maturity
• Work closely with experienced founders and technical leadership
• Help improve reliability for mission-critical messaging infrastructure
• Join a team that invests in each other and works hard to get better together

$115,000 to $140,000

Remote (U.S. required)
Note: Final interview will be held in-person.