# Senior AI Systems Engineer **Company**: Adobe **Experience**: senior **Job type**: full-time **Salary**: $159,200 - $301,600 annually **Category**: Engineering **Industry**: Technology **Apply**: https://adobe.wd5.myworkdayjobs.com/en-US/external_experienced/job/San-Jose/Principal-AI-Systems-Engineer---C-----Applied-AI_R170076?utm_source=yubhub.co&utm_medium=jobs_feed&utm_campaign=apply **Canonical**: https://yubhub.co/jobs/job_7e984be8-342 ## Description We are looking for a Senior AI Systems Engineer with deep C++ expertise to 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, and production software architecture. You will design and build the native infrastructure, service integration layers, evaluation systems, and reliability mechanisms that allow AI-powered features to operate safely, predictably, and efficiently inside complex software products. **Responsibilities** **AI-Native Systems Architecture** - Design and build native C++ infrastructure that connects complex product codebases to AI-powered services, agents, and model-backed workflows. - Define clean execution interfaces, schemas, validation layers, and error-handling contracts for AI-driven actions. - Create reliable bridges between product capabilities, AI orchestration systems, and backend services. - Ensure AI-initiated actions behave safely, predictably, and consistently within existing product workflows. - Guide long-term architecture decisions through ADRs, design documents, technical reviews, and cross-functional alignment. **C++ Platform and Integration Engineering** - Build high-quality C++ components for performance-sensitive, cross-platform environments. - Own critical client-side infrastructure such as service connectivity, session lifecycle, authentication, TLS, reconnection, concurrency, and async execution. - Design APIs and abstractions that are maintainable, testable, and scalable across multiple product surfaces. - Improve code health through modernization, refactoring, better testing, and stronger engineering patterns. - Balance performance, memory safety, reliability, backward compatibility, and developer experience in a mature codebase. **Applied AI Reliability and Evaluation** - Design systems that make AI features measurable, debuggable, and production-ready. - Build evaluation frameworks for AI workflows, including automated task execution, output validation, regression testing, scoring, and human review loops. - Define guardrails for AI-driven actions, including safety checks, capability boundaries, fallback paths, and failure handling. - Create privacy-conscious tracing, observability, and diagnostics for model-backed systems. - Partner with product, data science, security, legal, and AI governance teams to ensure AI capabilities meet quality, safety, and compliance expectations. **Technical Leadership** - Set engineering direction in ambiguous and fast-moving technical areas. - Influence architecture across native clients, backend AI services, orchestration layers, and product experience teams. - Help teams adopt AI-assisted engineering workflows for code generation, debugging, testing, documentation, and review. **Requirements** - 10+ years of professional software engineering experience, with significant depth in C++. - Strong experience building or maintaining large, mature, performance-sensitive codebases. - Expertise in modern C++ design, memory management, concurrency, API design, debugging, and systems-level performance. - Experience building cross-platform software across Windows, macOS, Linux, or similar environments. - Hands-on experience integrating AI, LLMs, agents, or model-backed systems into production or production-adjacent software. - Practical understanding of AI system failure modes, including hallucination, tool-calling errors, incomplete context, multi-turn drift, nondeterminism, and unreliable outputs. - Experience designing reliable interfaces between AI systems and deterministic software systems. - Strong systems architecture skills, including tradeoff analysis, technical strategy, and architecture documentation. - Experience with testing at scale, including unit tests, integration tests, CI validation, regression testing, and quality gates. - Ability to lead through influence across engineering, product, design, platform, security, and data science teams. - Strong written and verbal communication skills, with the ability to explain complex technical decisions to both engineering and executive audiences. **Preferred Qualifications** - Experience with frontier model APIs such as GPT, Claude, Gemini, or similar systems. - Experience designing tool/function-calling interfaces, agentic workflows, or AI orchestration systems. - Experience building AI evaluation frameworks, automated scoring systems, or human-in-the-loop quality review. - Familiarity with JSON-RPC, gRPC, WebSockets, REST, or similar service protocols. - Experience with observability and tracing for AI systems or distributed systems. - Experience with privacy-aware telemetry, data retention, secure client/service communication, or enterprise compliance requirements. - Familiarity with sandboxing, safety boundaries, permissions, or policy enforcement for AI-initiated actions. - Experience modernizing legacy C++ systems or improving developer productivity in large engineering organizations. - Background in creative tools, productivity applications, developer tools, enterprise software, or complex desktop applications. **What Makes This Role Special** - You will help define how AI becomes a reliable part of complex production software systems. - You will work at the intersection of C++ systems engineering, applied AI, platform architecture, and product-scale impact. - You will shape infrastructure that enables AI-powered experiences across multiple teams and product surfaces. - You will influence both technical strategy and day-to-day engineering execution. - You will help raise the bar for how teams build, evaluate, secure, and operate AI systems in production. ## Skills ### Required - C++ - AI - systems engineering - software architecture - cross-platform development - performance optimization - memory management - concurrency - API design - debugging - testing - quality assurance - reliability engineering - technical leadership ### Nice to have - frontier model APIs - tool/function-calling interfaces - agentic workflows - AI orchestration systems - AI evaluation frameworks - automated scoring systems - human-in-the-loop quality review - JSON-RPC - gRPC - WebSockets - REST - observability and tracing - privacy-aware telemetry - data retention - secure client/service communication - enterprise compliance requirements - sandboxing - safety boundaries - permissions - policy enforcement --- Source: [Apply at adobe.wd5.myworkdayjobs.com](https://adobe.wd5.myworkdayjobs.com/en-US/external_experienced/job/San-Jose/Principal-AI-Systems-Engineer---C-----Applied-AI_R170076?utm_source=yubhub.co&utm_medium=jobs_feed&utm_campaign=apply)