Senior AI Systems Engineer

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.