Lead Application Modernization Engineer

At Liatrio, we don't just ship software — we enable real transformation.

We help large enterprises break free from legacy systems and truly enable AI across their organizations. We design and deliver secure, scalable, agentic AI-native platforms that reshape how teams build, deliver, and thrive at scale.

We live this every day by embedding deeply with clients to drive meaningful AI enablement — accelerating modernization, reducing risk, and creating lasting competitive advantage through production-grade AI systems. We use tools like Claude, Cursor, and Windsurf daily to move faster and deliver better outcomes.

If you're a technical leader who leads with AI and drives lasting change, this is where you belong.

We're looking for a AI App Modernization Lead 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 write the hard code, keep the team unblocked, and make sure the client always knows where things stand.

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 technical solutions within your workstream — designing the approach, documenting tradeoffs, articulating it clearly to clients, and leading your team through implementation

• Designing and building cloud-native services from legacy systems — decomposing tightly coupled monoliths into APIs and services, migrating data, and keeping production running throughout

• Building full-stack, production-grade applications — frontend interfaces, backend services, APIs, and the integrations that connect them across complex enterprise environments

• Writing and reviewing code across multiple languages and paradigms — setting the technical standard for your workstream through your own work, not just through direction

• Designing event-driven and microservices architectures that can scale, evolve, and be operated by teams beyond the ones that built them

• Integrating AI and LLM capabilities into client applications — building agentic workflows, RAG pipelines, and intelligent automation that ships to production and stays reliable

• Implementing CI/CD pipelines and delivery automation that give teams the confidence to ship frequently

• Making day-to-day architecture decisions within your scope and escalating the right ones to the account lead or architect when they have broader implications

• Identifying technical risk early and surfacing it clearly before it becomes a delivery problem

• Generating ideas, failing fast, and demonstrating with POCs

• Driving knowledge sharing in and out of client engagements

• Participating in business development

• Lead a small team of engineers — organizing work, breaking down tasks, pairing on hard problems, and keeping the team moving

• Uplift engineers through code review, pairing, and day-to-day technical mentorship

• Mentor junior team members through 1:1s, feedback, and guiding technical growth

• Serve as a technical point of contact for your scope — representing the work clearly to client engineers and project stakeholders

• Keep account leaders and architects up to date on concerns, blockers, and changes

• Adapt quickly to change and shift focus as required to meet customer needs

• Provide feedback on team performance and areas for growth

• You've built and shipped full-stack applications — greenfield and legacy modernization — and you have real depth in at least one part of the stack with enough breadth to work productively across the others

• You're fluent in multiple programming languages and paradigms — you write clean, testable, production-quality code and you know the difference between code that works and code that lasts

• You've delivered cloud-native solutions across greenfield builds and brownfield modernization — frontend, backend APIs, cloud-hosted services — and you can speak to the tradeoffs at each layer

• You've made real architecture decisions — designed systems under constraints, documented tradeoffs, and been accountable for what happened when those decisions met production

• You've worked inside enterprise environments with complex distributed systems and multi-cloud setups, and you know how to keep delivery moving despite the organizational friction that comes with them

• You can own code quality for a team — writing, reviewing, and raising the bar for the engineers around you without creating a bottleneck

• You're comfortable with cloud-native architecture, branching strategies, and CI/CD automation — and you understand enough about platform and infrastructure to make good application-layer decisions

• You've been embedded with or worked closely alongside 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

• You've shipped AI-powered features in production — you understand the full lifecycle from integration through monitoring and maintenance

• You use AI coding tools like Claude, Cursor, or Windsurf as a core part of how you work every day — to think faster, review smarter, and ship higher quality code

• You're comfortable working with retrieval-augmented generation, LLM orchestration, or agentic workflows — either hands-on or close enough to guide others doing the work