Lead Forward Deployed Engineer

About Us

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.

About the Role

We are seeking Lead Forward Deployed Engineers who thrive on shipping production software, solving complex systems problems, and pioneering AI-first engineering workflows.

As a Lead Forward Deployed Engineer (FDE), you own the technical execution and architecture for your workstream. Leading a small team of engineers, you will deliver high-impact software while embedded directly within client engineering teams. In this role, you will partner closely with client leadership and account leads to align delivery with strategic goals, model AI-first engineering practices, and elevate client teams through active pairing and mentorship.

What You'll Do

Owning the technical delivery, architecture, and code quality for your workstream: making key technical decisions, documenting tradeoffs, and ensuring the team builds coherent, maintainable systems

Writing and reviewing production code across the full stack: setting the technical bar, reviewing PRs, and staying actively involved in direct implementation alongside your team

Integrating AI and LLM capabilities into client applications: designing and implementing agentic workflows, RAG pipelines, intelligent automation, and AI-augmented developer tooling

Pioneering AI-assisted software delivery: using advanced AI coding environments, LLM tooling, and agentic assistants to accelerate refactoring, code generation, and test writing in client codebases

Enabling client engineering teams on AI-first practices: hands-on coaching and pairing with client developers to integrate AI coding assistants into their daily development workflows and culture

Breaking down monolithic legacy applications into cloud-native microservices and event-driven architectures without taking critical systems offline

Anticipating technical debt, delivery friction, and architectural risk early: establishing clear mitigation strategies, test automation standards, and CI/CD best practices

Serving as the primary technical point of contact for your workstream: engaging directly with client engineering managers and technical directors on execution, delivery risk, and technical strategy

Mentoring and uplifting client and Liatrio engineers: pairing on complex problems, conducting architectural reviews, breaking down complex tasks, and providing continuous feedback

Partnering with account leadership and architects on technical scoping, statement of work (SOW) development, proof-of-concept (POC) demonstrations, and identifying expansion opportunities

Experience and Skills

Engineering and Architecture

You have a track record of owning technical execution and architectural direction for engineering teams in complex enterprise environments

You've modernized large legacy applications, with practical experience applying, incremental refactoring, and event-driven decomposition under real constraints

You are fluent across the full delivery stack (frontend, backend, APIs, data pipelines, and cloud infrastructure) with genuine technical depth in multiple core areas

You've designed and delivered cloud-native, distributed systems at enterprise scale: microservices, event-driven architectures, API gateways, and asynchronous messaging

You possess strong practical knowledge of platform engineering, infrastructure as code, cloud platform adoption (Kubernetes, managed container services), and CI/CD delivery automation

You know how to maintain a high engineering bar across a team: evaluating code, catching edge cases early, enforcing test standards, and driving velocity

AI and Intelligent Systems

You've built or integrated production AI capabilities into real applications, understanding the end-to-end lifecycle from model integration and retrieval pipelines to observability and maintenance

You actively model AI-augmented engineering workflows, leveraging modern AI coding tools as a daily multiplier for delivery speed and code quality

You can speak credibly with client technical leadership about pragmatic AI adoption and where intelligent workflows create genuine, production-grade leverage

Requirements

8+ years of hands-on software engineering experience, with demonstrated technical leadership of engineering teams or workstreams

Must be authorized to work in the United States or Canada without sponsorship

Travel availability: 25% depending on client needs