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 AI-enabled Application Modernization Engineers passionate about modernizing legacy software, building cloud-native and AI-augmented systems, and helping both client teams and our own engineers improve quality and speed of delivery. You will act as both a builder and an enabler — writing production-grade code and uplifting the engineers around you on modern AI-augmented ways of working.
You'll be embedded with enterprise clients building real software — modernizing systems that have been running the business for years and building new ones that need to run it for years to come. Day to day that looks like: Breaking down monolithic legacy applications and rebuilding them as cloud-native services — designing APIs, decomposing tightly coupled systems, and migrating data without taking the business offlineBuilding full-stack, production-grade applications — frontend interfaces, backend services, REST and GraphQL APIs, and the integrations that tie them together in complex enterprise environmentsWriting clean, testable, well-structured code across multiple languages and paradigms — and reviewing others' code with the same standardDesigning and implementing event-driven and microservices architectures that can scale, evolve, and be maintained by teams who didn't build themIntegrating AI and LLM capabilities directly into client applications — building agentic workflows, RAG pipelines, AI-augmented developer tooling, and intelligent automation that actually works in productionSetting up and improving CI/CD pipelines, test automation, and delivery infrastructure so teams can ship with confidenceWorking alongside Operations teams to make sure what gets built can actually be run — containerized, observable, and operable in cloud environmentsMentoring and uplifting the engineers around you — pairing, code review, and real-time feedback that makes the whole team better Keeping account leaders and architects informed of technical risk, blockers, and changes that affect the engagement Experience and Skills: Engineering: You've built production applications from scratch and modernized legacy systems — comfortable with both greenfield and brownfield, and know when approaches like strangler fig or lift-and-refactor are appropriateYou're fluent in multiple programming languages and paradigms — clean, testable code in both functional and object-oriented styles, knowing how to pick the right tool for the jobYou've delivered full-stack solutions — frontend web apps, backend APIs, cloud-hosted services, and standalone applications — and understand how those pieces fit together end-to-end in complex enterprise environmentsYou've worked inside large enterprise environments with distributed systems and multi-cloud setups — you know how to navigate organizational complexity and deliver in spite of itYou're comfortable owning your part of the SDLC end-to-end — writing code, reviewing PRs, writing tests, and empathizing with developers on either side of youYou understand cloud-native architecture — containerization, microservices, event-driven patterns — and are comfortable with source control branching strategies and CI/CD automationYou've either built or been closely embedded with Operations teams — you understand cloud-native platform adoption, whether that's Kubernetes, managed container services, or other orchestration platforms depending on client environment, infrastructure as code, observability, and what it means to build software that can actually be run in production AI and Intelligent Systems: You've built or integrated AI capabilities into real applications — you know what it takes to get an LLM-powered feature into production and keep it workingYou use AI coding tools like Claude, Cursor, or Windsurf as a natural part of how you work — as a way to move faster and produce higher quality output every dayYou have familiarity with retrieval-augmented generation, vector databases, or semantic search — either from building it or working alongside someone who has
5+ years of hands-on software engineering experienceMust be authorized to work in the United States or Canada without sponsorshipTravel availability: 25-50% depending on client needs