Senior Software Engineer

Senior Software Engineer / Research Engineer, AI SystemsLocation: San Francisco or New YorkWork Policy: 5 days per week in-officeCompensation: $200K to $400K base + competitive equityVisa: US work authorization requiredAbout the RoleA rapidly scaling AI company is building out a new engineering team focused on the infrastructure that governs how production AI agents reason, execute, use tools, and interact with users.This is a highly technical role sitting between distributed systems, backend engineering, and applied AI.You will work on the execution layer behind production agents, including model routing, planning, tool orchestration, control systems, experimentation, and real-time infrastructure.The problems are highly experimental and change quickly as underlying model capabilities evolve.What You’ll Work OnDesign and build execution frameworks for production AI agentsBuild systems for routing and orchestrating multiple modelsDevelop control-plane logic for planning, execution, and tool invocationBuild reliable distributed systems handling large volumes of real-time interactionsOptimize systems for latency, reliability, and production correctnessDiagnose real-world agent failures and identify root causesBuild feedback loops that improve agent behaviour over timeDevelop online experimentation and A/B testing infrastructureContribute to offline evaluation and simulation systemsImprove observability, testing, and production monitoringWork on real-time systems with strict latency requirementsContinuously rethink architecture as model capabilities improveWhat They’re Looking ForStrong backend or distributed systems engineering experienceExperience owning technically complex systems from design through productionStrong ability to debug difficult production problemsExperience improving reliability, performance, and observabilityComfortable operating in ambiguous environments where the solution is not already knownStrong technical judgement and ability to iterate quicklyExperience working closely with research, infrastructure, and product teamsEvidence of high technical trajectory and increasing ownershipParticularly Relevant ExperienceStrong candidates may have worked on:Distributed systemsBackend platformsAI infrastructureAgent systems or execution frameworksModel serving or inference infrastructureSearch or retrieval systemsReal-time systemsControl planesExperimentation platformsEvaluation infrastructureHigh-performance infrastructureQuantitative or technically demanding engineering environmentsDirect agent experience is valuable, but not mandatory.Exceptional engineers from strong systems, infrastructure, startup, or quantitative backgrounds can also be highly relevant.The Engineering ProblemsThe core challenge is not simply calling an LLM.It is building everything around the model that determines whether an intelligent system actually works reliably in production.That includes:ExecutionDetermining which workflows, models, and tools should run and in what order.OrchestrationCoordinating multiple models and components across complex tasks.ReliabilityEnsuring agent behaviour remains predictable and correct across millions of interactions.LatencyMaking intelligent systems respond quickly enough for real-time applications.ExperimentationUnderstanding why systems fail, testing improvements, and measuring whether changes actually work.AdaptabilityContinuously redesigning infrastructure as frontier models improve.Why Consider ItFrontier technical problemsYou will work on problems where established engineering patterns do not always exist yet.Significant ownershipThe team is being built out now, creating substantial scope for individual engineers to influence architecture and technical direction.High technical barThe team is targeting engineers from strong startups, infrastructure organizations, quantitative environments, and leading technical institutions.Production impactThe systems you build directly determine how AI agents reason, take actions, and behave in live environments.Rapid growthThe team plans to add approximately 6 to 8 engineers, creating opportunities for early hires to take on significant scope as it scales.CompensationBase salary: $200K to $400KAdditional compensation: Competitive equityTypical leveling ranges approximately from:Mid-level: $250K to $280KSenior: $300K to $330KStaff: $350K to $400KFinal compensation depends on experience, technical depth, and level.