Lead Forward Deployed Engineer

Job description

**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