Principal AI Systems Engineer — C++ / Applied AI
The Opportunity
We are looking for a Principal AI Systems Engineer with deep C++expertiseto help build the next generation of AI-enabled product and platform capabilities.
This role sits at the intersection of large-scale systems engineering, applied AI, andproductionsoftware architecture. You will design and build the native infrastructure, service integration layers, evaluation systems, and reliability mechanisms that allow AI-powered features tooperatesafely, predictably, and efficiently inside complex software products.
This is not a research-only role and not a prompt-engineering role. This is a hands-on principal engineering role for someone who can move between architecture, production code, AI system design, technical strategy, and cross-team leadership.
The ideal candidate is a strong C++ engineer first, with practical AI fluency: someone who understands how modern AI systems behave, where they fail, how to integrate them into production workflows, and how to design systems that make AI useful, reliable, observable, and secure.
WhatYou’llDo
AI-Native Systems Architecture
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Design and build native C++ infrastructure that connects complex product codebases to AI-powered services, agents, and model-backed workflows.
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Define clean execution interfaces, schemas, validation layers, and error-handling contracts for AI-driven actions.
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Create reliable bridges between product capabilities, AI orchestration systems, and backend services.
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Ensure AI-initiated actionsbehavesafely, predictably, and consistently within existing product workflows.
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Guidelong-term architecture decisions through ADRs, design documents, technical reviews, and cross-functional alignment.
C++ Platform and Integration Engineering
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Build high-quality C++ components for performance-sensitive, cross-platform environments.
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Own critical client-side infrastructure such as service connectivity, session lifecycle, authentication, TLS, reconnection, concurrency, and async execution.
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Design APIs and abstractions that are maintainable, testable, and scalable across multiple product surfaces.
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Improvecodehealth through modernization, refactoring, better testing, and stronger engineering patterns.
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Balance performance, memory safety, reliability, backward compatibility, and developer experience in a mature codebase.
Applied AI Reliability and Evaluation
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Design systems that make AI features measurable,debuggable, andproduction-ready.
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Build evaluation frameworks for AI workflows, including automated task execution, output validation, regression testing, scoring, and human review loops.
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Define guardrails for AI-driven actions, including safety checks, capability boundaries, fallback paths, and failure handling.
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Create privacy-conscious tracing, observability, and diagnostics for model-backed systems.
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Partner with product, data science, security, legal, and AI governance teams to ensure AI capabilities meet quality, safety, and compliance expectations.
Technical Leadership
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Act as a technical lead across teams building AI-powered product infrastructure.
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Set engineering direction in ambiguous and fast-moving technical areas.
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Influence architecture across native clients, backend AI services, orchestration layers, and product experience teams.
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Mentor senior engineers and raise the quality bar for AI systems, C++ engineering, and production reliability.
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Help teams adopt AI-assisted engineering workflows for code generation, debugging, testing, documentation, and review.
WhatYou’llBring
Required Qualifications
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10+ years of professional software engineering experience, with significant depth in C++.
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Strong experience building ormaintaininglarge, mature, performance-sensitive codebases.
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Expertisein modern C++ design, memory management, concurrency, API design, debugging, and systems-level performance.
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Experience building cross-platform software across W