42m ago

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Principal Forward Deployed Engineer

United StatesRemoteFull-timelead

Software EngineerSoftware Engineering

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Quick Summary

Requirements Summary

Write, review, and improve production code across critical systems while establishing high standards for architecture, security, reliability, maintainability, and performance.

Technical Tools

Software EngineerSoftware Engineering

In this senior, remote engineering role, you will lead enterprise-wide technical strategy and deliver transformative AI solutions for complex client environments. You will combine hands-on software engineering with architectural leadership to modernize legacy systems, build scalable cloud-native platforms, and integrate production-ready AI capabilities. Working directly with enterprise engineering teams and executive stakeholders, you will translate strategic objectives into practical technical roadmaps and measurable business outcomes. You will champion AI-first development practices, leveraging advanced coding assistants and agentic systems to accelerate software delivery and improve engineering productivity. Through technical mentorship, architectural guidance, and collaborative problem-solving, you will help client organizations adopt sustainable, secure, and scalable engineering practices. This opportunity is ideal for an experienced technical leader who thrives on solving complex systems challenges, influencing executive decisions, and delivering meaningful transformation in enterprise environments.

Lead enterprise architecture and technical strategy: Define and drive architectural direction across complex client engagements, aligning technology decisions with business objectives, long-term scalability, resilience, and operational requirements.

Develop production-grade software: Write, review, and improve production code across critical systems while establishing high standards for architecture, security, reliability, maintainability, and performance.

Architect enterprise AI solutions: Design and implement scalable AI capabilities, including large language model (LLM) integrations, retrieval-augmented generation (RAG) platforms, agentic systems, AI governance frameworks, and developer productivity solutions.

Champion AI-assisted engineering: Apply advanced AI coding environments, developer assistants, and agentic tools to accelerate code generation, legacy refactoring, automated testing, and software delivery within real-world client codebases.

Modernize legacy applications: Lead incremental modernization initiatives, decomposing monolithic systems into cloud-native microservices and event-driven architectures while managing technical risk and business continuity.

Establish secure and reliable AI systems: Evaluate and implement AI safety measures, observability capabilities, evaluation frameworks, and security controls to ensure AI solutions are dependable and production-ready.

Drive engineering enablement: Work directly with client developers through hands-on coaching, pairing, and practical demonstrations to integrate AI-first practices into everyday engineering workflows and organizational culture.

Advise executive stakeholders: Serve as a senior technical partner to engineering leaders and executives, providing guidance on architectural trade-offs, risk mitigation, platform evolution, transformation priorities, and technical roadmaps.

Strengthen delivery governance: Establish engineering standards, automated testing practices, security guardrails, CI/CD pipelines, and delivery processes that promote consistency and quality across multiple teams.

Mentor engineering talent: Develop staff and lead engineers through architecture reviews, code reviews, strategic pairing, and hands-on technical guidance, strengthening engineering capabilities across client and internal teams.

Support strategic business development: Collaborate with executive account leaders on technical proposals, statements of work (SOWs), client presentations, and strategic account growth opportunities.

Deliver measurable transformation outcomes: Identify opportunities to improve developer productivity, accelerate modernization, reduce operational risk, and demonstrate the business value of AI-enabled engineering practices.

Requirements

~2 min read

Extensive software engineering experience: At least 10 years of hands-on software engineering experience, including significant responsibility for enterprise architecture, technical strategy, or principal-level engineering initiatives.

Enterprise architecture leadership: Proven experience owning architectural direction for complex engineering workstreams, making high-impact technical decisions, and remaining accountable for delivery outcomes.

Legacy modernization expertise: Practical experience modernizing large enterprise applications using incremental refactoring, the strangler fig pattern, event-driven decomposition, or similar approaches.

Full-stack technical fluency: Strong understanding of frontend and backend development, APIs, data systems, cloud infrastructure, and the software delivery lifecycle, with substantial technical depth in multiple areas.

Distributed systems expertise: Experience designing and delivering enterprise-scale cloud-native architectures, including microservices, API gateways, asynchronous messaging, event-driven systems, and distributed applications.

Cloud and platform engineering knowledge: Familiarity with multi-cloud environments, infrastructure as code, Kubernetes or managed container platforms, cloud-native infrastructure, and DevOps practices.

Enterprise AI implementation: Hands-on experience designing and deploying AI solutions, including LLM integrations, RAG pipelines, security controls, observability, and evaluation frameworks.

AI-enabled development practices: Experience using modern AI coding tools, developer assistants, or agentic workflows to improve engineering productivity, accelerate refactoring, generate code, and support automated testing.

Security and operational excellence: Ability to make informed architectural decisions that address reliability, security, scalability, maintainability, and the operational complexity of enterprise systems.

Technical quality and mentorship: Demonstrated ability to establish engineering standards, review architecture and code, identify risks early, and develop the capabilities of other engineers.

Executive communication: Strong communication and stakeholder management skills, with the ability to explain complex technical concepts, transformation strategies, and expected business outcomes to VP-level and C-level leaders.

Strategic and business-oriented thinking: Ability to connect technical investments with business priorities, transformation metrics, delivery performance, and measurable value.

Problem-solving and adaptability: Sound technical judgment, practical decision-making, and the ability to deliver results within complex enterprise environments involving legacy constraints and organizational dependencies.

Work authorization: Must be authorized to work in the United States or Canada without employer sponsorship.

Travel availability: Willingness to travel up to approximately 25%, depending on client needs.

Collaborative mindset: Ability to work effectively with client teams, internal engineering colleagues, and executive stakeholders while promoting inclusive, respectful, and collaborative working relationships.

What We Offer

~2 min read

Remote work arrangement: Work remotely while collaborating with enterprise clients and distributed engineering teams.

Senior-level technical leadership: Take ownership of high-impact architectural decisions and lead complex enterprise transformation initiatives.

Cutting-edge AI exposure: Work hands-on with advanced AI systems, LLMs, agentic architectures, and AI-assisted software development practices.

Meaningful client impact: Help established organizations modernize critical systems, improve developer productivity, and accelerate their adoption of AI.

Technical autonomy: Influence architecture, engineering standards, modernization strategies, and the implementation of production-grade solutions.

Professional growth: Expand your expertise in enterprise architecture, cloud-native engineering, AI integration, and large-scale digital transformation.

Leadership opportunities: Mentor experienced engineers, strengthen client engineering teams, and shape modern software delivery practices.

Strategic business exposure: Collaborate with senior client executives and contribute to technical roadmaps, transformation planning, and strategic account initiatives.

Inclusive workplace: Join an organization committed to equal opportunity, diversity, and an inclusive professional environment.

Accessibility and accommodations: Reasonable accommodations are available during the application process for eligible candidates who require them.

How Jobgether works:

We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team.

We appreciate your interest and wish you the best!

Why Apply Through Jobgether?

Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time.

#LI-CL1

✓Remote work arrangement: Work remotely while collaborating with enterprise clients and distributed engineering teams.

✓Senior-level technical leadership: Take ownership of high-impact architectural decisions and lead complex enterprise transformation initiatives.

✓Cutting-edge AI exposure: Work hands-on with advanced AI systems, LLMs, agentic architectures, and AI-assisted software development practices.

✓Meaningful client impact: Help established organizations modernize critical systems, improve developer productivity, and accelerate their adoption of AI.

✓Technical autonomy: Influence architecture, engineering standards, modernization strategies, and the implementation of production-grade solutions.

✓Professional growth: Expand your expertise in enterprise architecture, cloud-native engineering, AI integration, and large-scale digital transformation.

✓Leadership opportunities: Mentor experienced engineers, strengthen client engineering teams, and shape modern software delivery practices.

✓Strategic business exposure: Collaborate with senior client executives and contribute to technical roadmaps, transformation planning, and strategic account initiatives.

✓Inclusive workplace: Join an organization committed to equal opportunity, diversity, and an inclusive professional environment.

✓Accessibility and accommodations: Reasonable accommodations are available during the application process for eligible candidates who require them.