Principal Forward Deployed Engineer
New
J
JobgetherEnterprise AI
Workplace type: Remote; based in the United States.Full-TimePrincipal
Salary not disclosed
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Job Details
- Experience
- At least 10 years of hands-on software engineering experience.
- Required Skills
- KubernetesCI/CDMicroservicesDistributed Systems
Requirements
- At least 10 years of hands-on software engineering experience, including significant responsibility for enterprise architecture, technical strategy, or principal-level initiatives.
- Experience owning architectural direction for complex engineering workstreams and remaining accountable for delivery outcomes.
- Practical experience modernizing large enterprise applications through incremental refactoring, the strangler fig pattern, event-driven decomposition, or similar approaches.
- Strong understanding of frontend and backend development, APIs, data systems, cloud infrastructure, and the software delivery lifecycle, with substantial depth in multiple areas.
- Experience designing enterprise-scale cloud-native architectures, including microservices, API gateways, asynchronous messaging, event-driven systems, and distributed applications.
- Knowledge of multi-cloud environments, infrastructure as code, Kubernetes or managed container platforms, cloud-native infrastructure, and DevOps practices.
- Hands-on experience designing and deploying AI solutions, including LLM integrations, RAG pipelines, security controls, observability, and evaluation frameworks.
- Experience using AI coding tools, developer assistants, or agentic workflows to improve engineering productivity, refactoring, code generation, and automated testing.
- Ability to make architectural decisions addressing reliability, security, scalability, maintainability, and operational complexity.
- Demonstrated ability to establish engineering standards, review architecture and code, identify risks, and develop other engineers.
- Strong communication and stakeholder management skills, including explaining technical concepts and business outcomes to VP-level and C-level leaders.
- Must be authorized to work in the United States or Canada without employer sponsorship; willing to travel up to approximately 25%, depending on client needs.
Responsibilities
- Lead architectural direction and technical strategy across complex client engagements.
- Write, review, and improve production code while setting standards for security, reliability, maintainability, and performance.
- Design and implement enterprise AI capabilities, including LLM integrations, RAG platforms, agentic systems, and AI governance frameworks.
- Use AI coding environments and agentic tools to accelerate code generation, legacy refactoring, testing, and software delivery.
- Modernize legacy applications through incremental modernization, cloud-native microservices, and event-driven architectures.
- Implement AI safety measures, observability, evaluation frameworks, and security controls.
- Coach client developers through hands-on guidance, pairing, and demonstrations.
- Advise engineering leaders and executives on architecture, risk, platform evolution, and technical roadmaps.
- Establish engineering standards, automated testing practices, security guardrails, CI/CD pipelines, and delivery processes.
- Mentor engineers and collaborate on technical proposals, client presentations, and strategic account opportunities.
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