Senior 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 hands-on engineer who leads with AI and drives lasting change, this is where you belong.

 

About the Role

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.

 

What You'll Do

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 offline

• Building full-stack, production-grade applications — frontend interfaces, backend services, REST and GraphQL APIs, and the integrations that tie them together in complex enterprise environments

• Writing clean, testable, well-structured code across multiple languages and paradigms — and reviewing others' code with the same standard

• Designing and implementing event-driven and microservices architectures that can scale, evolve, and be maintained by teams who didn't build them

• Integrating AI and LLM capabilities directly into client applications — building agentic workflows, RAG pipelines, AI-augmented developer tooling, and intelligent automation that actually works in production

• Setting up and improving CI/CD pipelines, test automation, and delivery infrastructure so teams can ship with confidence

• Working alongside Operations teams to make sure what gets built can actually be run — containerized, observable, and operable in cloud environments

• Mentoring 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 appropriate

• You'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 job

• You'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 environments

• You'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 it

• You'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 you

• You understand cloud-native architecture — containerization, microservices, event-driven patterns — and are comfortable with source control branching strategies and CI/CD automation

• You've either built or been closely embedded with Operations teams — you understand cloud-native platform adoption, whether that's Kuber