Principal Forward Deployed Engineer

Accountabilities:

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:
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.
Benefits:
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.