Liatrio
At Liatrio, we enable real transformation. We help industry-leading enterprises break free from legacy systems and adopt AI that reshapes how teams build, deliver, and thrive at scale. We partner directly with enterprise teams to embed AI-native practices into delivery by accelerating modernization, reducing risk, and shipping production-grade AI systems that set the standard for the industry. Our people embed directly inside client organizations, leading hands-on AI enablement and transformations that reshape how entire enterprises build and operate at scale. If you’re ready to lead real AI transformation, this is where you belong.
We're looking for a Lead Platform Engineer who owns a portion of the technical scope on a workstream, architects the solutions within it, and leads a small team of engineers to deliver against it. You work closely under the guidance of an account lead or architect — you're not setting the overall engagement strategy, but you are designing the solutions, making the day-to-day architecture calls, and being accountable for the technical quality of what your team ships. You're in the pipelines, writing IaC, building platform environments, and setting the standard through your own work while keeping the team unblocked and the client informed.
Technical Delivery and Oversight: You'll own a defined portion of the technical scope — designing the architecture, doing the work, and leading your team through it. That looks like: Architecting Platform solutions within your workstream — designing the approach, documenting tradeoffs, articulating it clearly to clients, and leading your team through implementationBuilding, configuring, and maintaining CI/CD pipelines end-to-end — designing the strategy, choosing the toolchain, and evolving it as the client's delivery maturity growsWriting and managing infrastructure as code — Terraform or CloudFormation — including module design, state management, and driftDesigning, writing, and managing AI Agents and AI tooling at scale or an organization as part of expanding platform capabilitiesBuilding and deploying cloud-native platform environments — whether that's Kubernetes, managed container services, or other orchestration platforms depending on client environment — getting teams to a place where they can run and operate workloads in production confidentlyBuilding and implementing observability — metrics, logging, tracing, and alerting that actually tells you something useful when things go wrongBuilding developer platform tooling, automation, and self-service infrastructure that makes engineering teams faster and less dependent on manual workIntegrating AI tooling into Platform workflows and delivery pipelines where it makes the most impactMaking day-to-day architecture decisions within your scope and escalating the right ones to the account lead or architect when they have broader implicationsIdentifying technical risk early and surfacing it clearly before it becomes a delivery problemGenerating ideas, failing fast, and demonstrating with POCs Team and People: Lead a small team of engineers — organizing work, breaking down tasks, pairing on hard problems, and keeping the team movingUplift engineers through code review, pairing, and day-to-day technical mentorshipMentor junior team members through 1:1s, feedback, and guiding technical growth Stakeholder Communication: Serve as a technical point of contact for your scope — representing the work clearly to client engineers and project stakeholdersKeep account leaders and architects up to date on concerns, blockers, and changesAdapt quickly to change and shift focus as required to meet customer needsProvide feedback on team performance and areas for growth Experience and Skills: Engineering and Infrastructure: You can own a CI/CD pipeline end-to-end — designing the strategy, building it, and evolving it as the client's delivery maturity growsYou've written and managed production IaC at scale — Terraform or CloudFormation — including module design, remote state, and managing infrastructure drift in a live enterprise environmentYou've built and deployed cloud-native platform environments in real production settings — whether that's Kubernetes, managed container services, or other orchestration platforms — and helped engineering teams get to a place where they can run and operate their workloads confidentlyYou've made real architecture decisions — designed systems under constraints, documented tradeoffs, and been accountable for what happened when those decisions met productionYou've built meaningful observability for real systems — you know the difference between metrics that tell a story and dashboards nobody looks at, and you can set up alerting that pages on the right thingsYou've built platform tooling and developer infrastructure — self-service tooling, automation, or internal infrastructure that made engineering teams faster and less dependent on manual ops workYou've worked deeply across at least one major cloud provider and have enough breadth across others to be productive quickly in a new environmentYou can hold the technical bar for a small team — reviewing code, catching architecture problems early, and helping engineers grow through the process AI and Intelligent Systems: You've integrated AI capabilities into real delivery workflows — whether that's AI-assisted pipeline troubleshooting, intelligent automation, or tooling that makes your team faster — and you can describe what worked and what didn'tYou use AI coding tools like Claude, Cursor, or Windsurf as a daily driver and actively help your team get value from themYou're familiar enough with LLM capabilities to make smart decisions about where to apply them in a Platform context
7+ years of hands-on Platform engineering experience, with some demonstrated technical leadershipMust be authorized to work in the United States or Canada without sponsorshipTravel: 25-50% depending on client needs and remote work otherwiseBase Salary: 140,000-170,000 plus 10% bonus