Principal Application Modernization Engineer

About Liatrio

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.

About the Role

The Principal Application Modernization Engineer is a senior technical leader who defines the scope of technical work, owns the architectural direction of complex workstreams, and is accountable for the technical outcomes of the engagement. 

You operate in ambiguity and make it clear. You walk into a legacy codebase, a stalled migration, or a cloud-native effort that's lost its footing, and you quickly develop a credible read on what's actually happening and what needs to change. You make the hard technical calls — and communicate them in a way that builds trust with both the engineers executing the work and the technical leaders on the client side.

What You'll Do

Technical Ownership and Architecture

• Define the scope of technical work related to deliverables and milestones of the engagement

• Own the architectural direction of your workstream — making key technical decisions, documenting tradeoffs, and ensuring the team is building toward something coherent and maintainable

• Responsible for code quality, architecture, and technical direction across the team

• Write and review production code across the stack — your technical judgment sets the bar, and you're in the work alongside the team

• Integrate AI and LLM capabilities into client applications — designing the architecture for agentic workflows, RAG pipelines, intelligent automation, and AI-augmented developer tooling, and guiding your team through implementation

• Anticipate technical risk before it becomes delivery risk — surface issues early, define mitigation strategies, and communicate proactively

• Participate in scoping discussions and SOW architecture for new and existing customers

• Generate ideas, be willing to fail fast, and demonstrate with POCs

• Drive knowledge sharing in and out of client engagements

Client Technical Engagement

• Serve as the senior technical point of contact for your workstream — engaging directly with client engineering managers and directors on architecture, delivery strategy, and technical risk

• Build trusted relationships with client technical leaders

• Proactively identify opportunities to improve engineering practices and technical quality at the client, and drive that change

• Participate in business development including client expansion conversations and SOW development

Team Leadership and Development

• Responsible and accountable for the technical outcomes of your team

• Write monthly feedback for all engineers on your workstream in collaboration with the Delivery Lead

• Mentor engineers through real technical challenges — pairing on hard problems, reviewing architecture decisions, giving feedback that raises their game

• Organize and break down complex work so the team can execute with clarity

• Share responsibility for the morale and well-being of the Liatrio team on your engagement

Experience and Skills

Engineering and Architecture

• You have a track record of owning the architectural direction of complex workstreams in enterprise environments — you've made the hard technical calls, been accountable for the outcomes, and learned from the experiences that didn't go as planned

• You've modernized large legacy applications in real enterprise environments — you understand the strangler fig pattern, incremental refactoring, and event-driven decomposition as practical strategies you've applied under real constraints

• You're fluent across the full delivery stack — frontend, backend, APIs, data, cloud infrastructure — with genuine depth in multiple areas

• You've designed and delivered cloud-native, distributed systems at enterprise scale — microservices, event-driven architectures, API gateways, async messaging — and you understand the failure modes and operational complexity that comes with them

• You've operated in large enterprise environments with multi-cloud setups, complex organizational structures, and legacy constraints — and you know how to deliver meaningful progress despite them

• You can hold the technical bar for an entire workstream — reviewing architecture, reviewing code, catching problems early, and developing engineers through the process

• You have enough knowledge of platform engineering, infrastructure as code, cloud-native platform adoption — whether that's Kubernetes, managed container services, or other orchestration platforms depending on client environment — and DevOps practices to make good architectural decisions and speak credibly to the engineers responsible for the platform

AI and Intelligent Systems

• You've built or integrated AI capabilities — you understand the full picture from integration through deployment, observability, and the ongoing work of keeping AI-powered features reliable

• You can have a credible conversation with client technical leaders about where AI creates genuine leverage — grounded in what's real